Resources

• Flight Plan Information Exchange using SWIM: https://upcommons.upc.edu/bitstream/handle/2117/117718/Flight%20Plan%20Information%20Exchange%20using%20SWIM.pdf?sequence=1&isAllowed=y

• Heatmaps: https://traffic-viz.github.io/scenarios/heatmaps.html

• Impala Shell: https://traffic-viz.github.io/scenarios/covid19.html
• Paramiko: https://stackoverflow.com/questions/16811581/python-paramiko-hangs-when-trying-to-execute-commands-over-ssh
• Documentation: https://opensky-network.org/datasets/covid-19/README-COVID-DATA.md
• Traffic Stuff: https://traffic-viz.github.io/opensky_impala.html#traffic.data.adsb.opensky_impala.Impala.flightlist
• EuroControl NM: https://traffic-viz.github.io/airac_usage.html?highlight=nm%20directory#airspaces-from-eurocontrol-nm
• Appending Dataframes: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.append.html
• Combining Dataframes: https://datacarpentry.org/python-ecology-lesson/05-merging-data/
• Airplanes: https://www.planespotters.net/hex/407177
• Press Command+Shift+Dot
• Documentation: https://buildmedia.readthedocs.org/media/pdf/traffic-viz/stable/traffic-viz.pdf
• Visualizing Trajectories: https://traffic-viz.github.io/quickstart.html?highlight=transform
• Projections: https://traffic-viz.github.io/quickstart.html?highlight=transform
• Dataframe to Pickle: https://www.w3resource.com/pandas/dataframe/dataframe-to_pickle.php
• ADS-B data – OpenSky Impala shell: https://traffic-viz.github.io/opensky_impala.html?highlight=switzerland
• DateTime to Day: https://stackoverflow.com/questions/41455967/convert-datetime-string-to-new-columns-of-day-month-year-in-pandas-data-frame
• Category List: https://stackoverflow.com/questions/52404971/get-a-list-of-categories-of-categorical-variable-python-pandas
• Airports: https://ourairports.com/help/data-dictionary.html

More Resources

• Plotting Occurrences per Date: https://stackoverflow.com/questions/58320398/plotting-the-count-of-occurrences-per-date
• Converting datetime to numeric: https://stackoverflow.com/questions/14524322/how-to-convert-a-date-string-to-different-format
• Matplotlib chart with count: https://stackoverflow.com/questions/56181597/matplotlib-line-chart-with-count
• Dataframe Count: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.count.html
• Plotly: How to plot grouped results on multiple lines?: https://stackoverflow.com/questions/57502469/plotly-how-to-plot-grouped-results-on-multiple-lines

Installations

pip install --upgrade traffic

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Requirement already satisfied: webencodings in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic) (0.5.1)
Collecting networkx>=1.9.0
  Downloading networkx-2.6.3-py3-none-any.whl (1.9 MB)
     |████████████████████████████████| 1.9 MB 5.7 MB/s eta 0:00:01     |█████▉                          | 348 kB 5.7 MB/s eta 0:00:01
Building wheels for collected packages: Cartopy, metar, pyModeS, scikit-fuzzy
  Building wheel for Cartopy (PEP 517) ... done
  Created wheel for Cartopy: filename=Cartopy-0.19.0.post1-cp39-cp39-macosx_10_9_x86_64.whl size=11841689 sha256=f30ec2353bdd3d5dee67c30fa73942d40e6699ffbc213d9bbc544e6d9b56e162
  Stored in directory: /Users/aliciaadams/Library/Caches/pip/wheels/62/5f/37/ccea2ef7b25fa05ef912f6b02fcb0af1e2bb1226420228d869
  Building wheel for metar (setup.py) ... done
  Created wheel for metar: filename=metar-1.8.0-py3-none-any.whl size=198771 sha256=7de26226697862a0d76d295d98afe134cc5f27ee05acccd95ceddb0e67570908
  Stored in directory: /Users/aliciaadams/Library/Caches/pip/wheels/9b/f1/2d/bb11fc8dd3996a5ab5a6d5ae4cf15577bc0b738876573aaa3f
  Building wheel for pyModeS (setup.py) ... done
  Created wheel for pyModeS: filename=pyModeS-2.9-py3-none-any.whl size=67393 sha256=d9f434f0a97310c9fb1dfeb5a2d676ac6144e4d4ce15e25d3d69e012b53463ba
  Stored in directory: /Users/aliciaadams/Library/Caches/pip/wheels/ea/87/3c/6fdb2ed7e6c0c148d4655fc1fb92277bfb9f4c679318e2716a
  Building wheel for scikit-fuzzy (setup.py) ... done
  Created wheel for scikit-fuzzy: filename=scikit_fuzzy-0.4.2-py3-none-any.whl size=894089 sha256=d1bc5939532de0813eba87a995bdac68e751e5ab34b45adee5a77307a7d83524
  Stored in directory: /Users/aliciaadams/Library/Caches/pip/wheels/32/2c/a1/a90a7d7dd8448ec029f298a61f3490275e99b17aa348be675c
Successfully built Cartopy metar pyModeS scikit-fuzzy
Installing collected packages: click, pytz, munch, cligj, click-plugins, urllib3, pyproj, pandas, networkx, idna, fiona, cryptography, charset-normalizer, traittypes, tqdm, toolz, soupsieve, scikit-fuzzy, requests, pyyaml, pyOpenSSL, pynacl, geopandas, Cartopy, bcrypt, appdirs, typing-extensions, requests-pkcs12, pyModeS, pyarrow, paramiko, openap, metar, lxml, ipyleaflet, cartes, beautifulsoup4, altair, traffic
  Attempting uninstall: Cartopy
    Found existing installation: Cartopy 0.18.0
    Uninstalling Cartopy-0.18.0:
      Successfully uninstalled Cartopy-0.18.0
Successfully installed Cartopy-0.19.0.post1 altair-4.1.0 appdirs-1.4.4 bcrypt-3.2.0 beautifulsoup4-4.10.0 cartes-0.5 charset-normalizer-2.0.7 click-8.0.3 click-plugins-1.1.1 cligj-0.7.2 cryptography-35.0.0 fiona-1.8.20 geopandas-0.10.2 idna-3.3 ipyleaflet-0.14.0 lxml-4.6.4 metar-1.8.0 munch-2.5.0 networkx-2.6.3 openap-1.2 pandas-1.3.4 paramiko-2.8.0 pyModeS-2.9 pyOpenSSL-20.0.1 pyarrow-4.0.1 pynacl-1.4.0 pyproj-3.3.0 pytz-2021.3 pyyaml-6.0 requests-2.26.0 requests-pkcs12-1.13 scikit-fuzzy-0.4.2 soupsieve-2.3.1 toolz-0.11.2 tqdm-4.62.3 traffic-2.6.6 traittypes-0.2.1 typing-extensions-3.10.0.2 urllib3-1.26.7
Note: you may need to restart the kernel to use updated packages.

pip install traffic_qtgui  

Collecting traffic_qtgui
  Downloading traffic_qtgui-1.1-py3-none-any.whl (162 kB)
     |████████████████████████████████| 162 kB 2.2 MB/s eta 0:00:01
Requirement already satisfied: traffic<3.0.0,>=2.6.4 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic_qtgui) (2.6.6)
Requirement already satisfied: pyOpenSSL<21.0.0,>=20.0.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic_qtgui) (20.0.1)
Collecting PyQt5<6.0.0,>=5.15.4
  Downloading PyQt5-5.15.6-cp36-abi3-macosx_10_13_x86_64.whl (7.0 MB)
     |████████████████████████████████| 7.0 MB 4.6 MB/s eta 0:00:01
Requirement already satisfied: cryptography>=3.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pyOpenSSL<21.0.0,>=20.0.1->traffic_qtgui) (35.0.0)
Requirement already satisfied: six>=1.5.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pyOpenSSL<21.0.0,>=20.0.1->traffic_qtgui) (1.16.0)
Requirement already satisfied: cffi>=1.12 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from cryptography>=3.2->pyOpenSSL<21.0.0,>=20.0.1->traffic_qtgui) (1.14.6)
Requirement already satisfied: pycparser in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from cffi>=1.12->cryptography>=3.2->pyOpenSSL<21.0.0,>=20.0.1->traffic_qtgui) (2.21)
Collecting PyQt5-Qt5>=5.15.2
  Downloading PyQt5_Qt5-5.15.2-py3-none-macosx_10_13_intel.whl (40.5 MB)
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Collecting PyQt5-sip<13,>=12.8
  Downloading PyQt5_sip-12.9.0-cp39-cp39-macosx_10_9_x86_64.whl (63 kB)
     |████████████████████████████████| 63 kB 2.5 MB/s eta 0:00:011
Requirement already satisfied: beautifulsoup4<5.0.0,>=4.9.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.10.0)
Requirement already satisfied: lxml<5.0.0,>=4.6.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.6.4)
Requirement already satisfied: pyproj<4.0.0,>=3.1.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.3.0)
Requirement already satisfied: Shapely<2.0.0,>=1.7.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.7.1)
Requirement already satisfied: metar<2.0.0,>=1.8.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.8.0)
Requirement already satisfied: pandas<2.0.0,>=1.2.4 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.3.4)
Requirement already satisfied: ipywidgets<8.0.0,>=7.6.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (7.6.5)
Requirement already satisfied: pyModeS<3.0,>=2.9 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.9)
Requirement already satisfied: matplotlib<4.0.0,>=3.4.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.5.0)
Requirement already satisfied: appdirs<2.0.0,>=1.4.4 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.4.4)
Requirement already satisfied: typing-extensions<4.0.0,>=3.10.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.10.0.2)
Requirement already satisfied: tqdm<5.0.0,>=4.61.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.62.3)
Requirement already satisfied: pyarrow<5.0,>=4.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.0.1)
Requirement already satisfied: openap<2.0,>=1.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.2)
Requirement already satisfied: numpy<2.0,>=1.18 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.21.4)
Requirement already satisfied: requests-pkcs12<2.0,>=1.10 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.13)
Requirement already satisfied: Cartopy<0.20.0,>=0.19.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.19.0.post1)
Requirement already satisfied: requests<3.0.0,>=2.25.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.26.0)
Requirement already satisfied: scipy<2.0.0,>=1.7.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.7.2)
Requirement already satisfied: altair<5.0.0,>=4.1.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.1.0)
Requirement already satisfied: paramiko<3.0.0,>=2.7.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.8.0)
Requirement already satisfied: ipyleaflet<0.15.0,>=0.14.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.14.0)
Requirement already satisfied: cartes<1.0,>=0.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.5)
Requirement already satisfied: entrypoints in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.3)
Requirement already satisfied: jinja2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.0.2)
Requirement already satisfied: jsonschema in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.2.0)
Requirement already satisfied: toolz in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.11.2)
Requirement already satisfied: soupsieve>1.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from beautifulsoup4<5.0.0,>=4.9.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.3.1)
Requirement already satisfied: geopandas in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.10.2)
Requirement already satisfied: importlib-metadata in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.8.1)
Requirement already satisfied: pyshp>=2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from Cartopy<0.20.0,>=0.19.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.1.3)
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Requirement already satisfied: widgetsnbextension~=3.5.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.5.1)
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Requirement already satisfied: nbformat>=4.2.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (5.1.3)
Requirement already satisfied: ipython-genutils~=0.2.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.2.0)
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Requirement already satisfied: ipykernel>=4.5.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (6.4.1)
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Requirement already satisfied: tornado<7.0,>=4.2 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (6.1)
Requirement already satisfied: appnope in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.1.2)
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Requirement already satisfied: nest-asyncio>=1.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from jupyter-client<8.0->ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.5.1)
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Requirement already satisfied: packaging>=20.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from matplotlib<4.0.0,>=3.4.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (21.0)
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Requirement already satisfied: pyparsing>=2.2.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from matplotlib<4.0.0,>=3.4.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.0.4)
Requirement already satisfied: cycler>=0.10 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from matplotlib<4.0.0,>=3.4.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.11.0)
Requirement already satisfied: fonttools>=4.22.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from matplotlib<4.0.0,>=3.4.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.28.1)
Requirement already satisfied: attrs>=17.4.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from jsonschema->altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (21.2.0)
Requirement already satisfied: pyrsistent>=0.14.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from jsonschema->altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.18.0)
Requirement already satisfied: scikit-fuzzy in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from openap<2.0,>=1.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.4.2)
Requirement already satisfied: pyyaml in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from openap<2.0,>=1.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (6.0)
Requirement already satisfied: pytz>=2017.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pandas<2.0.0,>=1.2.4->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2021.3)
Requirement already satisfied: pynacl>=1.0.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from paramiko<3.0.0,>=2.7.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.4.0)
Requirement already satisfied: bcrypt>=3.1.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from paramiko<3.0.0,>=2.7.2->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.2.0)
Requirement already satisfied: ptyprocess>=0.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pexpect>4.3->ipython>=4.0.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.7.0)
Requirement already satisfied: wcwidth in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=4.0.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.2.5)
Requirement already satisfied: certifi in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pyproj<4.0.0,>=3.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2021.10.8)
Requirement already satisfied: idna<4,>=2.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests<3.0.0,>=2.25.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.3)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests<3.0.0,>=2.25.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.26.7)
Requirement already satisfied: charset-normalizer~=2.0.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests<3.0.0,>=2.25.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.0.7)
Requirement already satisfied: notebook>=4.4.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (6.4.6)
Requirement already satisfied: nbconvert in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (6.1.0)
Requirement already satisfied: terminado>=0.8.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.9.4)
Requirement already satisfied: prometheus-client in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.12.0)
Requirement already satisfied: Send2Trash>=1.8.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.8.0)
Requirement already satisfied: argon2-cffi in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (20.1.0)
Requirement already satisfied: fiona>=1.8 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from geopandas->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.8.20)
Requirement already satisfied: click>=4.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from fiona>=1.8->geopandas->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (8.0.3)
Requirement already satisfied: cligj>=0.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from fiona>=1.8->geopandas->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.7.2)
Requirement already satisfied: munch in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from fiona>=1.8->geopandas->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.5.0)
Requirement already satisfied: click-plugins>=1.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from fiona>=1.8->geopandas->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.1.1)
Requirement already satisfied: zipp>=0.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from importlib-metadata->cartes<1.0,>=0.5->traffic<3.0.0,>=2.6.4->traffic_qtgui) (3.6.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from jinja2->altair<5.0.0,>=4.1.0->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.0.1)
Requirement already satisfied: jupyterlab-pygments in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.1.2)
Requirement already satisfied: bleach in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (4.0.0)
Requirement already satisfied: pandocfilters>=1.4.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.4.3)
Requirement already satisfied: nbclient<0.6.0,>=0.5.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.5.3)
Requirement already satisfied: defusedxml in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.7.1)
Requirement already satisfied: testpath in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.5.0)
Requirement already satisfied: mistune<2,>=0.8.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.8.4)
Requirement already satisfied: async-generator in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (1.10)
Requirement already satisfied: webencodings in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets<8.0.0,>=7.6.3->traffic<3.0.0,>=2.6.4->traffic_qtgui) (0.5.1)
Requirement already satisfied: networkx>=1.9.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from scikit-fuzzy->openap<2.0,>=1.1->traffic<3.0.0,>=2.6.4->traffic_qtgui) (2.6.3)
Installing collected packages: PyQt5-sip, PyQt5-Qt5, PyQt5, traffic-qtgui
Successfully installed PyQt5-5.15.6 PyQt5-Qt5-5.15.2 PyQt5-sip-12.9.0 traffic-qtgui-1.1
Note: you may need to restart the kernel to use updated packages.

conda install --channel conda-forge cartopy

Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: /Users/aliciaadams/opt/anaconda3/envs/Flights

  added / updated specs:
    - cartopy


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    brotli-1.0.9               |       h0d85af4_6          18 KB  conda-forge
    brotli-bin-1.0.9           |       h0d85af4_6          17 KB  conda-forge
    ca-certificates-2021.10.8  |       h033912b_0         139 KB  conda-forge
    cartopy-0.18.0             |   py39hf1ba7ce_1         1.7 MB
    certifi-2021.10.8          |   py39h6e9494a_1         145 KB  conda-forge
    cycler-0.11.0              |     pyhd8ed1ab_0          10 KB  conda-forge
    fonttools-4.28.1           |   py39h89e85a6_0         1.5 MB  conda-forge
    freetype-2.10.4            |       h4cff582_1         890 KB  conda-forge
    jbig-2.1                   |    h0d85af4_2003          42 KB  conda-forge
    kiwisolver-1.3.2           |   py39hf018cea_1          59 KB  conda-forge
    lcms2-2.12                 |       h577c468_0         404 KB  conda-forge
    lerc-2.2.1                 |       h046ec9c_0         164 KB  conda-forge
    libblas-3.9.0              |12_osx64_openblas          12 KB  conda-forge
    libbrotlicommon-1.0.9      |       h0d85af4_6          63 KB  conda-forge
    libbrotlidec-1.0.9         |       h0d85af4_6          33 KB  conda-forge
    libbrotlienc-1.0.9         |       h0d85af4_6         324 KB  conda-forge
    libcblas-3.9.0             |12_osx64_openblas          12 KB  conda-forge
    libdeflate-1.7             |       h35c211d_5          67 KB  conda-forge
    libgfortran-5.0.0          |9_3_0_h6c81a4c_23          19 KB  conda-forge
    libgfortran5-9.3.0         |      h6c81a4c_23         1.7 MB  conda-forge
    liblapack-3.9.0            |12_osx64_openblas          12 KB  conda-forge
    libopenblas-0.3.18         |openmp_h3351f45_0         9.0 MB  conda-forge
    libtiff-4.3.0              |       h1167814_1         621 KB  conda-forge
    libwebp-base-1.2.1         |       h0d85af4_0         692 KB  conda-forge
    llvm-openmp-12.0.1         |       hda6cdc1_1         287 KB  conda-forge
    lz4-c-1.9.3                |       he49afe7_1         155 KB  conda-forge
    matplotlib-base-3.5.0      |   py39hb07454d_0         7.4 MB  conda-forge
    munkres-1.1.4              |     pyh9f0ad1d_0          12 KB  conda-forge
    numpy-1.21.4               |   py39h7eed0ac_0         5.8 MB  conda-forge
    olefile-0.46               |     pyh9f0ad1d_1          32 KB  conda-forge
    openssl-1.1.1l             |       h0d85af4_0         1.9 MB  conda-forge
    pillow-7.2.0               |   py39h31b929e_2         634 KB  conda-forge
    python_abi-3.9             |           2_cp39           4 KB  conda-forge
    scipy-1.7.2                |   py39h056f1c0_0        20.0 MB  conda-forge
    shapely-1.7.1              |   py39h9250791_0         376 KB
    zstd-1.5.0                 |       h582d3a0_0         583 KB  conda-forge
    ------------------------------------------------------------
                                           Total:        54.6 MB

The following NEW packages will be INSTALLED:

  brotli             conda-forge/osx-64::brotli-1.0.9-h0d85af4_6
  brotli-bin         conda-forge/osx-64::brotli-bin-1.0.9-h0d85af4_6
  cartopy            pkgs/main/osx-64::cartopy-0.18.0-py39hf1ba7ce_1
  cycler             conda-forge/noarch::cycler-0.11.0-pyhd8ed1ab_0
  fonttools          conda-forge/osx-64::fonttools-4.28.1-py39h89e85a6_0
  freetype           conda-forge/osx-64::freetype-2.10.4-h4cff582_1
  geos               pkgs/main/osx-64::geos-3.8.0-hb1e8313_0
  jbig               conda-forge/osx-64::jbig-2.1-h0d85af4_2003
  kiwisolver         conda-forge/osx-64::kiwisolver-1.3.2-py39hf018cea_1
  lcms2              conda-forge/osx-64::lcms2-2.12-h577c468_0
  lerc               conda-forge/osx-64::lerc-2.2.1-h046ec9c_0
  libblas            conda-forge/osx-64::libblas-3.9.0-12_osx64_openblas
  libbrotlicommon    conda-forge/osx-64::libbrotlicommon-1.0.9-h0d85af4_6
  libbrotlidec       conda-forge/osx-64::libbrotlidec-1.0.9-h0d85af4_6
  libbrotlienc       conda-forge/osx-64::libbrotlienc-1.0.9-h0d85af4_6
  libcblas           conda-forge/osx-64::libcblas-3.9.0-12_osx64_openblas
  libdeflate         conda-forge/osx-64::libdeflate-1.7-h35c211d_5
  libgfortran        conda-forge/osx-64::libgfortran-5.0.0-9_3_0_h6c81a4c_23
  libgfortran5       conda-forge/osx-64::libgfortran5-9.3.0-h6c81a4c_23
  liblapack          conda-forge/osx-64::liblapack-3.9.0-12_osx64_openblas
  libopenblas        conda-forge/osx-64::libopenblas-0.3.18-openmp_h3351f45_0
  libtiff            conda-forge/osx-64::libtiff-4.3.0-h1167814_1
  libwebp-base       conda-forge/osx-64::libwebp-base-1.2.1-h0d85af4_0
  llvm-openmp        conda-forge/osx-64::llvm-openmp-12.0.1-hda6cdc1_1
  lz4-c              conda-forge/osx-64::lz4-c-1.9.3-he49afe7_1
  matplotlib-base    conda-forge/osx-64::matplotlib-base-3.5.0-py39hb07454d_0
  munkres            conda-forge/noarch::munkres-1.1.4-pyh9f0ad1d_0
  numpy              conda-forge/osx-64::numpy-1.21.4-py39h7eed0ac_0
  olefile            conda-forge/noarch::olefile-0.46-pyh9f0ad1d_1
  pillow             conda-forge/osx-64::pillow-7.2.0-py39h31b929e_2
  proj               conda-forge/osx-64::proj-6.2.1-h773a61f_0
  pyshp              conda-forge/noarch::pyshp-2.1.3-pyh44b312d_0
  python_abi         conda-forge/osx-64::python_abi-3.9-2_cp39
  scipy              conda-forge/osx-64::scipy-1.7.2-py39h056f1c0_0
  shapely            pkgs/main/osx-64::shapely-1.7.1-py39h9250791_0
  zstd               conda-forge/osx-64::zstd-1.5.0-h582d3a0_0

The following packages will be UPDATED:

  certifi            pkgs/main::certifi-2021.10.8-py39hecd~ --> conda-forge::certifi-2021.10.8-py39h6e9494a_1

The following packages will be SUPERSEDED by a higher-priority channel:

  ca-certificates    pkgs/main::ca-certificates-2021.10.26~ --> conda-forge::ca-certificates-2021.10.8-h033912b_0
  openssl              pkgs/main::openssl-1.1.1l-h9ed2024_0 --> conda-forge::openssl-1.1.1l-h0d85af4_0



Downloading and Extracting Packages
openssl-1.1.1l       | 1.9 MB    | ##################################### | 100% 
libtiff-4.3.0        | 621 KB    | ##################################### | 100% 
fonttools-4.28.1     | 1.5 MB    | ##################################### | 100% 
certifi-2021.10.8    | 145 KB    | ##################################### | 100% 
shapely-1.7.1        | 376 KB    | ##################################### | 100% 
freetype-2.10.4      | 890 KB    | ##################################### | 100% 
libwebp-base-1.2.1   | 692 KB    | ##################################### | 100% 
lz4-c-1.9.3          | 155 KB    | ##################################### | 100% 
matplotlib-base-3.5. | 7.4 MB    | ##################################### | 100% 
munkres-1.1.4        | 12 KB     | ##################################### | 100% 
cycler-0.11.0        | 10 KB     | ##################################### | 100% 
brotli-1.0.9         | 18 KB     | ##################################### | 100% 
olefile-0.46         | 32 KB     | ##################################### | 100% 
libbrotlidec-1.0.9   | 33 KB     | ##################################### | 100% 
kiwisolver-1.3.2     | 59 KB     | ##################################### | 100% 
llvm-openmp-12.0.1   | 287 KB    | ##################################### | 100% 
pillow-7.2.0         | 634 KB    | ##################################### | 100% 
zstd-1.5.0           | 583 KB    | ##################################### | 100% 
brotli-bin-1.0.9     | 17 KB     | ##################################### | 100% 
scipy-1.7.2          | 20.0 MB   | ##################################### | 100% 
libdeflate-1.7       | 67 KB     | ##################################### | 100% 
libbrotlicommon-1.0. | 63 KB     | ##################################### | 100% 
libcblas-3.9.0       | 12 KB     | ##################################### | 100% 
numpy-1.21.4         | 5.8 MB    | ##################################### | 100% 
lerc-2.2.1           | 164 KB    | ##################################### | 100% 
python_abi-3.9       | 4 KB      | ##################################### | 100% 
libgfortran-5.0.0    | 19 KB     | ##################################### | 100% 
lcms2-2.12           | 404 KB    | ##################################### | 100% 
ca-certificates-2021 | 139 KB    | ##################################### | 100% 
libbrotlienc-1.0.9   | 324 KB    | ##################################### | 100% 
jbig-2.1             | 42 KB     | ##################################### | 100% 
libopenblas-0.3.18   | 9.0 MB    | ##################################### | 100% 
libblas-3.9.0        | 12 KB     | ##################################### | 100% 
cartopy-0.18.0       | 1.7 MB    | ##################################### | 100% 
liblapack-3.9.0      | 12 KB     | ##################################### | 100% 
libgfortran5-9.3.0   | 1.7 MB    | ##################################### | 100% 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

Note: you may need to restart the kernel to use updated packages.

pip install folium

Collecting folium
  Downloading folium-0.12.1.post1-py2.py3-none-any.whl (95 kB)
     |████████████████████████████████| 95 kB 1.6 MB/s eta 0:00:01
Requirement already satisfied: numpy in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from folium) (1.21.4)
Collecting branca>=0.3.0
  Downloading branca-0.4.2-py3-none-any.whl (24 kB)
Requirement already satisfied: jinja2>=2.9 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from folium) (3.0.2)
Requirement already satisfied: requests in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from folium) (2.26.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from jinja2>=2.9->folium) (2.0.1)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests->folium) (1.26.7)
Requirement already satisfied: certifi>=2017.4.17 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests->folium) (2021.10.8)
Requirement already satisfied: idna<4,>=2.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests->folium) (3.3)
Requirement already satisfied: charset-normalizer~=2.0.0 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from requests->folium) (2.0.7)
Installing collected packages: branca, folium
Successfully installed branca-0.4.2 folium-0.12.1.post1
Note: you may need to restart the kernel to use updated packages.

pip install xarray

Collecting xarray
  Downloading xarray-0.20.1-py3-none-any.whl (835 kB)
     |████████████████████████████████| 835 kB 1.7 MB/s eta 0:00:01
Requirement already satisfied: pandas>=1.1 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from xarray) (1.3.4)
Requirement already satisfied: numpy>=1.18 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from xarray) (1.21.4)
Requirement already satisfied: python-dateutil>=2.7.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pandas>=1.1->xarray) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from pandas>=1.1->xarray) (2021.3)
Requirement already satisfied: six>=1.5 in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas>=1.1->xarray) (1.16.0)
Installing collected packages: xarray
Successfully installed xarray-0.20.1
Note: you may need to restart the kernel to use updated packages.

pip install seaborn

Collecting seaborn
  Downloading seaborn-0.11.2-py3-none-any.whl (292 kB)
     |████████████████████████████████| 292 kB 1.6 MB/s eta 0:00:01
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Installing collected packages: seaborn
Successfully installed seaborn-0.11.2
Note: you may need to restart the kernel to use updated packages.

pip install plotly

Collecting plotly
  Using cached plotly-5.4.0-py2.py3-none-any.whl (25.3 MB)
Requirement already satisfied: six in ./opt/anaconda3/envs/Flights/lib/python3.9/site-packages (from plotly) (1.16.0)
Collecting tenacity>=6.2.0
  Using cached tenacity-8.0.1-py3-none-any.whl (24 kB)
Installing collected packages: tenacity, plotly
Successfully installed plotly-5.4.0 tenacity-8.0.1
Note: you may need to restart the kernel to use updated packages.

pip install squarify

Configuration

traffic.config_file

PosixPath('/Users/aliciaadams/Library/Application Support/traffic/traffic.conf')

Initialization

import numpy as np
import pandas as pd
import plotly.express as px
import seaborn as sns
import xarray
import squarify
import datetime
import plotly.graph_objects as go

from traffic.core import Traffic
from traffic.data import opensky, aircraft, airports, eurofirs
from traffic.data.samples import airbus_tree
from traffic.drawing import countries, lakes, ocean, rivers
from traffic.core.projection import Amersfoort, GaussKruger, Lambert93, EuroPP
from traffic.data.samples import quickstart
import traffic_qtgui as traffic_gui

import matplotlib as matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

from matplotlib.offsetbox import AnchoredText
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

import altair as alt

from cartopy.crs import TransverseMercator, EuroPP, PlateCarree
from cartes.crs import EuroPP
from cartes.osm import Nominatim

Successful Tests

Simple Traffic Calls

t_aib

Traffic with 1 identifiers

		count
icao24	callsign
388dfb	AIB04FI	8532

Digging into the reference databases

# This is a simple call of the airport information
    # and plan drawing. This airport is in the Netherlands
    # but I'd like to see if I can pull the same info for Glasgow

airports['EHAM']

Amsterdam Airport Schiphol (Netherlands) EHAM/AMS

# I wanted to see if I could use either code (EHAM or AMS) to call
    # the airport information
    
airports["AMS"]

Amsterdam Airport Schiphol (Netherlands) EHAM/AMS

# Airbus test flights from and to Toulouse airport
t_aib = opensky.history(
    "2019-11-01 09:00",
    "2019-11-01 12:00",
    departure_airport="LFBO",
    arrival_airport="LFBO",
    callsign="AIB%",
)

quickstart_id = Traffic.from_flights(
    flight.assign(flight_id=f"{flight.callsign}_{i:03}")
    for i, flight in enumerate(quickstart)
)
quickstart

Traffic with 397 identifiers

		count
icao24	callsign
4ca84d	RYR3YM	2859
393320	AFR27GH	2770
505c98	RAM667	2752
3944ef	HOP87DJ	2731
4ca574	IBK5111	2706
393322	AFR23FK	2665
40643a	EZY57FT	2656
394c18	AFR140W	2613
344692	VLG2972	2599
400cd1	EZY81GE	2579

# quickstart["GMA03"]  # on callsign
quickstart["40665e"]  # on icao24

flight = opensky.history(
    "2021-10-17",
    # stop is implicit, i.e. stop="2017-02-06"
    callsign="EZY96EM",
    return_flight=True
)

flight

Flight GMA03

• aircraft: 400dc2 · 🇬🇧 G-SASC (BE20)
• from: 2021-10-17 08:34:54+00:00
• to: 2021-10-17 17:26:43+00:00

flight = opensky.history(
    "2021-10-17", # no need to specify stop time; stop is implicit"
    callsign="GMA03",
    return_flight=True
)

eurofirs["LPPC"].geoencode()

Belevingsvlucht

I looked this up, and this translates to "Experience Flight" in Dutch. It appears to refer to the path and elevation lines recorded and plotted.

This data gives a useful background of the capabilities of the Traffic plug-in.

# This is a pre-loaded flight track, and I guess this command autoplots the data

from traffic.data.samples import belevingsvlucht

belevingsvlucht

Flight TRA051

• aircraft: 484506 · 🇳🇱 PH-HZO (B738)
• from: 2018-05-30 15:21:38+00:00
• to: 2018-05-30 20:22:56+00:00

# This is another pre-loaded test.
# see https://traffic-viz.github.io/samples.html if any issue on import
(
    airports["EHAM"].geoencode(runways=True, labels=True)
    + belevingsvlucht.first(minutes=1).geoencode().mark_line(color="steelblue")
    + belevingsvlucht.last(minutes=6).geoencode().mark_line(color="orangered")
).configure_text(font="Ubuntu", fontWeight="bold")

(
    airports["EHAM"].geoencode(runways=True, labels=True)
    + belevingsvlucht.first(minutes=1).geoencode().mark_line(color="steelblue")
    + belevingsvlucht.last(minutes=6).geoencode().mark_line(color="orangered")
).configure_text(font="Arial", fontWeight="bold")

with plt.style.context("traffic"):
    fig = plt.figure()

    # Choose the projection type
    ax0 = fig.add_subplot(221, projection=EuroPP())
    ax1 = fig.add_subplot(222, projection=Lambert93())
    ax2 = fig.add_subplot(223, projection=Amersfoort())
    ax3 = fig.add_subplot(224, projection=GaussKruger())

    for ax in [ax0, ax1, ax2, ax3]:
        ax.add_feature(countries())
        # Maximum extent for the map
        ax.set_global()
        # Remove border and set transparency for background
        ax.spines['geo'].set_visible(False)
        ax.background_patch.set_visible(False)

    # Flight.plot returns the result from Matplotlib as is
    # Here we catch it to reuse the color of each trajectory
    ret, *_ = quickstart["AFR27GH"].plot(ax0)
    quickstart["AFR27GH"].plot(
        ax1, color=ret.get_color(), linewidth=2
    )

    ret, *_ = belevingsvlucht.plot(ax0)
    belevingsvlucht.plot(
        ax2, color=ret.get_color(), linewidth=2
    )
    ret, *_ = airbus_tree.plot(ax0)
    airbus_tree.plot(
        ax3, color=ret.get_color(), linewidth=2
    )

    # We reduce here the extent of the EuroPP() map
    # between 8°W and 18°E, and 40°N and 60°N
    ax0.set_extent((-8, 18, 40, 60))

    params = dict(fontname="Ubuntu", fontsize=18, pad=12)

    ax0.set_title("EuroPP()", **params)
    ax1.set_title("Lambert93()", **params)
    ax2.set_title("Amersfoort()", **params)
    ax3.set_title("GaussKruger()", **params)

    fig.tight_layout()

/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1463165486.py:16: DeprecationWarning: The background_patch property is deprecated. Use GeoAxes.patch instead.
  ax.background_patch.set_visible(False)
WARNING:matplotlib.font_manager:findfont: Font family ['Ubuntu'] not found. Falling back to DejaVu Sans.

(
    belevingsvlucht.callsign,
    belevingsvlucht.icao24,
    belevingsvlucht.registration,
    belevingsvlucht.typecode,
)

('TRA051', '484506', 'PH-HZO', 'B738')

first30 = belevingsvlucht.first(minutes=30)
after19 = belevingsvlucht.after("2018-05-30 19:00", strict=False)

# Notice the "strict" comparison (>) vs. "or equal" comparison (>=)
print(f"between {first30.start:%H:%M:%S} and {first30.stop:%H:%M:%S}")
print(f"between {after19.start:%H:%M:%S} and {after19.stop:%H:%M:%S}")

# between 15:21:38 and 15:51:37
# between 19:00:00 and 20:22:56

between 15:21:38 and 15:51:37
between 19:00:00 and 20:22:56

between1920 = belevingsvlucht.between(
    "2018-05-30 19:00", "2018-05-30 20:00"
)
between1920

Flight TRA051

• aircraft: 484506 · 🇳🇱 PH-HZO (B738)
• from: 2018-05-30 19:00:01+00:00
• to: 2018-05-30 19:59:59+00:00

with plt.style.context("traffic"):
    fig, ax = plt.subplots(figsize=(10, 7))
    between1920.plot_time(
        ax, y=["altitude", "groundspeed"], secondary_y=["groundspeed"]
    )

# This plots all active flights at current time 
    # (re-ran at 7:32pm on Wednesday, December 8 so I could have a live timestamp)

sv = opensky.api_states()

with plt.style.context('traffic'):
    fig, ax = plt.subplots(subplot_kw=dict(projection=EuroPP()))
    ax.add_feature(countries())
    ax.gridlines()
    ax.set_extent((-7, 15, 40, 55))

    sv.plot(ax, s=10)

Glasgow Airports

airports.search('Glasgow')

	name	iata	icao	latitude	longitude	country	altitude	type	municipality
478	Glasgow Industrial Airport	NaN	07MT	48.421101	-106.528000	United States	2762.0	small_airport	Glasgow
2797	Blatter Airport	NaN	25MT	48.422199	-106.252998	United States	2800.0	small_airport	Glasgow
5565	Creek Side Landing Airport	NaN	4KY1	36.895000	-85.772797	United States	727.0	small_airport	Glasgow
8571	TJ Samson Hospital Heliport	NaN	7KY8	37.011784	-85.904846	United States	910.0	heliport	Glasgow
14881	Wokal Field/Glasgow-Valley County Airport	GGW	KGGW	48.212502	-106.614998	United States	2296.0	medium_airport	Glasgow
14895	Glasgow Municipal Airport	GLW	KGLW	37.031799	-85.953697	United States	716.0	small_airport	Glasgow
26959	Balcony Downs Airstrip	NaN	VA43	37.647400	-79.424797	United States	820.0	small_airport	Glasgow
26976	Twin River Airport	NaN	VA63	37.679434	-79.420200	United States	720.0	closed	Glasgow
28254	Glasgow City Heliport	NaN	EGEG	55.861389	-4.296944	United Kingdom	NaN	heliport	Glasgow
28362	Glasgow International Airport	GLA	EGPF	55.871899	-4.433060	United Kingdom	26.0	large_airport	Paisley, Renfrewshire
28367	Glasgow Prestwick Airport	PIK	EGPK	55.502003	-4.587019	United Kingdom	65.0	medium_airport	Prestwick, South Ayrshire
29159	Glasgow Seaplane Terminal	NaN	GB-0684	55.858310	-4.294882	United Kingdom	NaN	closed	Glasgow
29218	Glasgow Clyde Heliport	NaN	GB-0743	55.867760	-4.333120	United Kingdom	NaN	heliport	Glasco
48328	Aberdeen Hospital Heliport	NaN	CNG2	45.572301	-62.644300	Canada	75.0	heliport	New Glasgow
48547	Rodney (New Glasgow) Airport	NaN	CPU3	42.531932	-81.605937	Canada	670.0	small_airport	Rodney

# This uses the code for the Glasgow International Airport

airports['GLA']

Glasgow International Airport (United Kingdom) EGPF/GLA

None

# Gives me the lat and long of the airport
    # Just testing the database
    
airports["GLA"].latlon

(55.871899, -4.43306)

# and equating it to the list
dfCAC['destlat'] = 55.871899
dfCAC['destlong']= -4.433060
 
# Observe the result
dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date	destlat	destlong
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17	55.871899	-4.43306
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17	55.871899	-4.43306
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17	55.871899	-4.43306
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France	2021-11-14	55.871899	-4.43306
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz	2021-11-14	55.871899	-4.43306

1800 rows × 60 columns

fig, ax = plt.subplots(
    1, figsize=(15, 10),
     subplot_kw=dict(projection=TransverseMercator(10, 45))
)

ax.add_feature(countries(scale="50m"))
ax.add_feature(rivers(scale="50m"))
ax.add_feature(lakes(scale="50m"))
ax.add_feature(ocean(scale="50m"))

for name, fir in eurofirs.items():
    fir.plot(ax, edgecolor="#3a3aaa", lw=2, alpha=0.5)

    if name not in ["ENOB", "LPPO", "GCCC"]:
        fir.annotate(
            ax, s=name, ha="center", color="#3a3aaa"
        )

ax.set_extent((-20, 45, 30, 70))

ERROR:fiona._env:PROJ: proj_identify: /Users/aliciaadams/opt/anaconda3/envs/Flights/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.
ERROR:fiona._env:PROJ: proj_identify: /Users/aliciaadams/opt/anaconda3/envs/Flights/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.
ERROR:fiona._env:PROJ: proj_identify: /Users/aliciaadams/opt/anaconda3/envs/Flights/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.
ERROR:fiona._env:PROJ: proj_identify: /Users/aliciaadams/opt/anaconda3/envs/Flights/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.

aircraft['EXS32TE']

	icao24	registration	typecode	serialnumber	model	operator	operatoricao	owner

from cartopy.crs import EuroPP
from traffic.drawing import countries, rivers

flight = opensky.history(
    "2021-10-17 12:00",
    "2021-10-17 14:00",
    callsign='GMA03',
    count=True,
    return_flight=True
)

with plt.style.context('traffic'):
    fig, ax = plt.subplots(
        subplot_kw=dict(projection=EuroPP())
    )
    ax.add_feature(countries())
    ax.add_feature(rivers())
    ax.set_extent((-8, 57., 0., 55.))

    # no specific method for that in traffic
    # but switch back to pandas DataFrame for manual plot
    flight.data.plot.scatter(
            ax=ax, x='longitude', y='latitude', c='count',
            transform=PlateCarree(), grid=False, s=5, cmap='viridis'
    )

/Users/aliciaadams/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/plotting/_matplotlib/core.py:986: MatplotlibDeprecationWarning:

Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.

flight

Flight EZY158T

• aircraft: 406d95 · 🇬🇧 G-EZOP (A320)
• from: 2017-02-05 15:08:15+00:00
• to: 2017-02-05 16:59:59+00:00

airports["EIDW"].geoencode()

Other Tests

Creating a Database

https://traffic-viz.github.io/aircraft.html

df = opensky.api_arrival('EGPF', '2021-10-17 12:00', '2021-10-24 12:00')

df = opensky.api_arrival('EGPF', '2021-10-17 12:00', '2021-10-24 12:00')
# Arrivals at the Glasgow International Airport (IATA: GLA, ICAO: EGPF) between October 28, noon and October 30, noon.

df

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
414	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF
413	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF
412	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF
411	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	None	EGPF
410	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF
...	...	...	...	...	...	...
4	2021-10-24 09:12:22+00:00	2021-10-24 10:04:58+00:00	405ee1	SHT6L	EGLL	EGPF
3	2021-10-24 09:23:18+00:00	2021-10-24 10:12:49+00:00	400936	BAW9273	EGLL	EGPF
2	2021-10-24 09:39:48+00:00	2021-10-24 10:37:56+00:00	400d5a	BAW2512	EGKK	EGPF
1	2021-10-24 10:59:40+00:00	2021-10-24 11:27:58+00:00	406df5	GSGTS	None	EGPF
0	2021-10-24 11:32:57+00:00	2021-10-24 11:59:21+00:00	407567	EZY623V	EGAA	EGPF

415 rows × 6 columns

df.shape

(1800, 7)

df2 = opensky.api_arrival('EGPF', '2021-10-24 12:00', '2021-10-31 12:00')
# Arrivals at the Glasgow International Airport (IATA: GLA, ICAO: EGPF) between October 28, noon and October 30, noon.

df3 = df.append(df2, ignore_index=True)

df3

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	None	EGPF
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF
...	...	...	...	...	...	...
812	2021-10-31 10:15:54+00:00	2021-10-31 11:28:34+00:00	40631b	EZY493H	EGKK	EGPF
813	2021-10-31 10:01:32+00:00	2021-10-31 11:31:45+00:00	40643c	EZY84QK	LFPG	EGPF
814	2021-10-31 10:35:59+00:00	2021-10-31 11:34:59+00:00	407989	BZE05A	EGKB	EGPF
815	2021-10-31 10:41:52+00:00	2021-10-31 11:38:29+00:00	406b5a	BAW2512	EGKK	EGPF
816	2021-10-31 11:12:09+00:00	2021-10-31 11:44:15+00:00	407568	EZY576Z	EGAA	EGPF

817 rows × 6 columns

df4 = opensky.api_arrival('EGPF', '2021-10-31 12:00', '2021-11-07 12:00')
# Arrivals at the Glasgow International Airport (IATA: GLA, ICAO: EGPF) between October 28, noon and October 30, noon.

df4

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
544	2021-10-31 04:28:14+00:00	2021-10-31 12:09:44+00:00	89605e	ROJ004	None	EGPF
543	2021-10-31 07:16:54+00:00	2021-10-31 12:15:44+00:00	4c8061	CYP1630	LCLK	EGPF
542	2021-10-31 12:15:55+00:00	2021-10-31 12:44:10+00:00	406df4	GHIAL	None	EGPF
541	2021-10-31 10:02:26+00:00	2021-10-31 12:48:57+00:00	406b91	EZY75NT	LEAL	EGPF
540	2021-10-31 13:00:55+00:00	2021-10-31 13:12:52+00:00	406de9	CG199	EGPK	EGPF
...	...	...	...	...	...	...
4	2021-11-07 09:44:00+00:00	2021-11-07 11:18:09+00:00	406b91	EZY84QK	LFPG	EGPF
3	2021-11-07 10:15:46+00:00	2021-11-07 11:22:12+00:00	400a25	BAW2512	EGKK	EGPF
2	2021-11-06 18:27:29+00:00	2021-11-07 11:31:36+00:00	8960e0	UAE27	VTBS	EGPF
1	2021-11-07 11:12:03+00:00	2021-11-07 11:39:10+00:00	40768b	EZY576Z	EGAA	EGPF
0	2021-11-07 10:48:13+00:00	2021-11-07 11:48:41+00:00	4008e5	SHT6T	EGLL	EGPF

545 rows × 6 columns

df5 = df3.append(df4, ignore_index=True)

df5

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	None	EGPF
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF
...	...	...	...	...	...	...
1357	2021-11-07 09:44:00+00:00	2021-11-07 11:18:09+00:00	406b91	EZY84QK	LFPG	EGPF
1358	2021-11-07 10:15:46+00:00	2021-11-07 11:22:12+00:00	400a25	BAW2512	EGKK	EGPF
1359	2021-11-06 18:27:29+00:00	2021-11-07 11:31:36+00:00	8960e0	UAE27	VTBS	EGPF
1360	2021-11-07 11:12:03+00:00	2021-11-07 11:39:10+00:00	40768b	EZY576Z	EGAA	EGPF
1361	2021-11-07 10:48:13+00:00	2021-11-07 11:48:41+00:00	4008e5	SHT6T	EGLL	EGPF

1362 rows × 6 columns

df6 = opensky.api_arrival('EGPF', '2021-11-07 12:00', '2021-11-14 12:00')
# Arrivals at the Glasgow International Airport (IATA: GLA, ICAO: EGPF) between October 28, noon and October 30, noon.

df6

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
438	2021-11-07 12:39:30+00:00	2021-11-07 12:58:19+00:00	406df4	GHIAL	None	EGPF
437	2021-11-07 09:34:05+00:00	2021-11-07 13:57:06+00:00	4b9030	TRK9	LTAC	EGPF
436	2021-11-07 10:56:33+00:00	2021-11-07 14:07:19+00:00	4075bb	EXS7BY	LEAL	EGPF
435	2021-11-07 13:45:14+00:00	2021-11-07 14:23:46+00:00	4ca788	EIN226	EIDW	EGPF
434	2021-11-07 13:59:31+00:00	2021-11-07 14:27:59+00:00	40768b	EZY612D	EGAA	EGPF
...	...	...	...	...	...	...
4	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF
3	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF
2	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF
1	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF
0	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF

438 rows × 6 columns

df7 = df5.append(df6, ignore_index=True)

df7

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	None	EGPF
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF
...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF

1800 rows × 6 columns

df7.to_csv(r'EGPF_Flights.csv')

df = pd.read_csv('EGPF_Flights.csv')
df

	Unnamed: 0	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
0	0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF
1	1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF
2	2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF
3	3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF
4	4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF
...	...	...	...	...	...	...	...
1795	1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF
1796	1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF
1797	1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF
1798	1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF
1799	1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF

1800 rows × 7 columns

df.isna().sum()

# Only one icao24 null entry. Great.

Unnamed: 0               0
firstSeen                0
lastSeen                 0
icao24                   0
callsign                 0
estDepartureAirport    362
estArrivalAirport        0
dtype: int64

craft = pd.read_csv('aircraftDatabase-2021-12.csv')
craft

/Users/aliciaadams/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/IPython/core/interactiveshell.py:3444: DtypeWarning: Columns (14) have mixed types.Specify dtype option on import or set low_memory=False.
  exec(code_obj, self.user_global_ns, self.user_ns)

	icao24	registration	manufacturericao	manufacturername	model	typecode	serialnumber	linenumber	icaoaircrafttype	operator	...	status	built	firstflightdate	seatconfiguration	engines	modes	adsb	acars	notes	categoryDescription
0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
1	aa3487	N757F	NaN	Raytheon Aircraft Company	A36	NaN	E-3121	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
2	ae267b	6533	VOUGHT	Aerospatiale	MH-65C Dolphin	AS65	6182	NaN	H2T	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	No ADS-B Emitter Category Information
3	a4fa61	N42MH	NaN	Piper	PA-31-350	NaN	31-7852015	NaN	NaN	NaN	...	NaN	1977-01-01	NaN	NaN	LYCOMING TI0-540 SER	False	False	False	NaN	NaN
4	c04101	C-FYQA	NaN	Champion Aircraft Corporation	7GCA (Champion)	NaN	420	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
459995	a58188	N454FU	NaN	Dehavilland	BEAVER DHC-2 MK.1	NaN	1193	NaN	NaN	NaN	...	NaN	1957-01-01	NaN	NaN	P&W R-985 SERIES	False	False	False	NaN	NaN
459996	a41c24	N364LB	NaN	Lindstrand Balloons	90A	NaN	5009	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
459997	a5f755	N4839D	NaN	Cessna	182A	NaN	34939	NaN	NaN	NaN	...	NaN	1958-01-01	NaN	NaN	CONT MOTOR O-470 SERIES	False	False	False	NaN	NaN
459998	3980d5	F-HAGV	NaN	Cameron	Z-225 Hot Air Balloon	BALL	11499	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
459999	3fecd8	D-MWLV	IKARUS	Comco Ikarus	C42 Cyclone	C42	9907-6197	NaN	L1P	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	Ultralight / hang-glider / paraglider

460000 rows × 27 columns

craft.isna().sum()

# Only one icao24 null entry. Great.

icao24                      1
registration            37080
manufacturericao       314082
manufacturername        38321
model                   37360
typecode               287044
serialnumber            39809
linenumber             459050
icaoaircrafttype       314165
operator               438314
operatorcallsign       421409
operatoricao           420153
operatoriata           453676
owner                   40724
testreg                459710
registered             398363
reguntil               202446
status                 460000
built                  215862
firstflightdate        459736
seatconfiguration      460000
engines                198460
modes                       0
adsb                        0
acars                       0
notes                  459799
categoryDescription    342100
dtype: int64

Expanding the Database

# Referencing in an airport database

airports = pd.read_csv('airports.csv')
airports

	id	ident	type	name	latitude_deg	longitude_deg	elevation_ft	continent	iso_country	iso_region	municipality	scheduled_service	gps_code	iata_code	local_code	home_link	wikipedia_link	keywords
0	6523	00A	heliport	Total Rf Heliport	40.070801	-74.933601	11.0	NaN	US	US-PA	Bensalem	no	00A	NaN	00A	NaN	NaN	NaN
1	323361	00AA	small_airport	Aero B Ranch Airport	38.704022	-101.473911	3435.0	NaN	US	US-KS	Leoti	no	00AA	NaN	00AA	NaN	NaN	NaN
2	6524	00AK	small_airport	Lowell Field	59.947733	-151.692524	450.0	NaN	US	US-AK	Anchor Point	no	00AK	NaN	00AK	NaN	NaN	NaN
3	6525	00AL	small_airport	Epps Airpark	34.864799	-86.770302	820.0	NaN	US	US-AL	Harvest	no	00AL	NaN	00AL	NaN	NaN	NaN
4	6526	00AR	closed	Newport Hospital & Clinic Heliport	35.608700	-91.254898	237.0	NaN	US	US-AR	Newport	no	NaN	NaN	NaN	NaN	NaN	00AR
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
69192	46378	ZZ-0001	heliport	Sealand Helipad	51.894444	1.482500	40.0	EU	GB	GB-ENG	Sealand	no	NaN	NaN	NaN	http://www.sealandgov.org/	https://en.wikipedia.org/wiki/Principality_of_...	Roughs Tower Helipad
69193	307326	ZZ-0002	small_airport	Glorioso Islands Airstrip	-11.584278	47.296389	11.0	AF	TF	TF-U-A	Grande Glorieuse	no	NaN	NaN	NaN	NaN	NaN	NaN
69194	346788	ZZ-0003	small_airport	Fainting Goat Airport	32.110587	-97.356312	690.0	NaN	US	US-TX	Blum	no	87TX	NaN	87TX	NaN	NaN	NaN
69195	342102	ZZZW	closed	Scandium City Heliport	69.355287	-138.939310	4.0	NaN	CA	CA-YT	(Old) Scandium City	no	ZZZW	ZYW	YK96	NaN	NaN	NaN
69196	313629	ZZZZ	small_airport	Satsuma Iōjima Airport	30.784722	130.270556	338.0	AS	JP	JP-46	Mishima	no	RJX7	NaN	RJX7	NaN	http://wikimapia.org/6705190/Satsuma-Iwo-jima-...	SATSUMA,IWOJIMA,RJX7

69197 rows × 18 columns

# Referencing in a country database that appends the airport database

countries = pd.read_csv('countries.csv')
countries

	id	code	name	continent	wikipedia_link	keywords
0	302672	AD	Andorra	EU	https://en.wikipedia.org/wiki/Andorra	NaN
1	302618	AE	United Arab Emirates	AS	https://en.wikipedia.org/wiki/United_Arab_Emir...	UAE,مطارات في الإمارات العربية المتحدة
2	302619	AF	Afghanistan	AS	https://en.wikipedia.org/wiki/Afghanistan	NaN
3	302722	AG	Antigua and Barbuda	NaN	https://en.wikipedia.org/wiki/Antigua_and_Barbuda	NaN
4	302723	AI	Anguilla	NaN	https://en.wikipedia.org/wiki/Anguilla	NaN
...	...	...	...	...	...	...
242	302609	YT	Mayotte	AF	https://en.wikipedia.org/wiki/Mayotte	NaN
243	302610	ZA	South Africa	AF	https://en.wikipedia.org/wiki/South_Africa	NaN
244	302611	ZM	Zambia	AF	https://en.wikipedia.org/wiki/Zambia	NaN
245	302612	ZW	Zimbabwe	AF	https://en.wikipedia.org/wiki/Zimbabwe	NaN
246	302613	ZZ	Unknown or unassigned country	AF	https://en.wikipedia.org/wiki/Unknown_or_unass...	NaN

247 rows × 6 columns

df_craft = pd.merge(df, craft, how='left', on='icao24')
df_craft

	Unnamed: 0	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	...	status	built	firstflightdate	seatconfiguration	engines	modes	adsb	acars	notes	categoryDescription
0	0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	Large (75000 to 300000 lbs)
2	2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	...	NaN	2010-01-01	NaN	NaN	2 x INTERNATIONAL AERO ENGINE V2527-A5<br>	False	False	False	NaN	No ADS-B Emitter Category Information
3	3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	...	NaN	2005-01-01	NaN	NaN	2 x PRATT &amp; WHITNEY CANADA PT6A-42&nbsp;&n...	False	False	False	NaN	NaN
4	4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	...	NaN	2007-01-01	NaN	NaN	2x CFM CFM56-7B26	False	False	False	NaN	No ADS-B Emitter Category Information
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	...	NaN	2002-01-01	NaN	NaN	2 x INTERNATIONAL AERO ENGINE V2527-A5<br>	False	False	False	NaN	NaN
1796	1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	...	NaN	2014-01-01	NaN	NaN	2 x CFM CFM56-5B4/3<br>	False	False	False	NaN	No ADS-B Emitter Category Information
1797	1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	NaN
1798	1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	Large (75000 to 300000 lbs)
1799	1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	...	NaN	NaN	NaN	NaN	NaN	False	False	False	NaN	No ADS-B Emitter Category Information

1800 rows × 33 columns

dfCA = pd.merge(df_craft, airports, how='left', left_on='estDepartureAirport', right_on='ident')
dfCA

	Unnamed: 0	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	...	iso_country	iso_region	municipality	scheduled_service	gps_code	iata_code	local_code	home_link	wikipedia_link	keywords
0	0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	...	ES	ES-AN	Málaga	yes	LEMG	AGP	NaN	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga
1	1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	...	ES	ES-V	Alicante	yes	LEAL	ALC	NaN	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN
2	2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	...	GB	GB-ENG	London	yes	EGLL	LHR	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres
3	3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	...	IE	IE-D	Dublin	yes	EIDW	DUB	NaN	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	...	GB	GB-ENG	London	yes	EGKK	LGW	NaN	http://www.gatwickairport.com/	https://en.wikipedia.org/wiki/Gatwick_Airport	LON, Crawley, Charlwood
1796	1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	...	FR	FR-IDF	Paris	yes	LFPG	CDG	NaN	http://www.aeroportsdeparis.fr/	https://en.wikipedia.org/wiki/Charles_de_Gaull...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...
1797	1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	...	GB	GB-ENG	London	yes	EGLL	LHR	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres
1798	1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	...	GB	GB-NIR	Belfast	yes	EGAA	BFS	NaN	http://www.belfastairport.com/	https://en.wikipedia.org/wiki/Belfast_Internat...	Aldergrove, RAF Aldergrove
1799	1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	...	CH	CH-GE	Geneva	yes	LSGG	GVA	NaN	http://www.gva.ch/	https://en.wikipedia.org/wiki/Geneva_Cointrin_...	NaN

1800 rows × 52 columns

dfCAC = pd.merge(dfCA, countries, how='left', left_on='iso_country', right_on='code')
dfCAC

	Unnamed: 0	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	...	local_code	home_link	wikipedia_link_x	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y
0	0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	...	NaN	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
1	1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	...	NaN	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
2	2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
3	3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	...	NaN	NaN	NaN	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN
4	4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	...	NaN	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	...	NaN	http://www.gatwickairport.com/	https://en.wikipedia.org/wiki/Gatwick_Airport	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1796	1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	...	NaN	http://www.aeroportsdeparis.fr/	https://en.wikipedia.org/wiki/Charles_de_Gaull...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France
1797	1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1798	1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	...	NaN	http://www.belfastairport.com/	https://en.wikipedia.org/wiki/Belfast_Internat...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1799	1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	...	NaN	http://www.gva.ch/	https://en.wikipedia.org/wiki/Geneva_Cointrin_...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz

1800 rows × 58 columns

dfCAC.to_csv(r'Flights_Appended.csv')

dfCAC = pd.read_csv('Flights_Appended.csv')
dfCAC

	Unnamed: 0	Unnamed: 0.1	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	...	local_code	home_link	wikipedia_link_x	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y
0	0	0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	...	NaN	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
1	1	1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	...	NaN	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
2	2	2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
3	3	3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	...	NaN	NaN	NaN	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN
4	4	4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	...	NaN	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	1795	1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	...	NaN	http://www.gatwickairport.com/	https://en.wikipedia.org/wiki/Gatwick_Airport	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1796	1796	1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	...	NaN	http://www.aeroportsdeparis.fr/	https://en.wikipedia.org/wiki/Charles_de_Gaull...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France
1797	1797	1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1798	1798	1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	...	NaN	http://www.belfastairport.com/	https://en.wikipedia.org/wiki/Belfast_Internat...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1799	1799	1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	...	NaN	http://www.gva.ch/	https://en.wikipedia.org/wiki/Geneva_Cointrin_...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz

1800 rows × 59 columns

dfCAC = dfCAC.drop('Unnamed: 0.1', 1)

/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2854381171.py:1: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only
  dfCAC = dfCAC.drop('Unnamed: 0.1', 1)

dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	local_code	home_link	wikipedia_link_x	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	NaN	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	NaN	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	NaN	NaN	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	NaN	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	NaN	http://www.gatwickairport.com/	https://en.wikipedia.org/wiki/Gatwick_Airport	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	NaN	http://www.aeroportsdeparis.fr/	https://en.wikipedia.org/wiki/Charles_de_Gaull...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	NaN	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	NaN	http://www.belfastairport.com/	https://en.wikipedia.org/wiki/Belfast_Internat...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	NaN	http://www.gva.ch/	https://en.wikipedia.org/wiki/Geneva_Cointrin_...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz

1800 rows × 57 columns

dfCAC["lastSeen"] = pd.to_datetime(dfCAC["lastSeen"])

dfCAC["day"] = dfCAC['lastSeen'].map(lambda x: x.day)

dfCAC["date"] = dfCAC['lastSeen'].map(lambda x: x.date)

dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	home_link	wikipedia_link_x	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	NaN	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	http://www.gatwickairport.com/	https://en.wikipedia.org/wiki/Gatwick_Airport	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	http://www.aeroportsdeparis.fr/	https://en.wikipedia.org/wiki/Charles_de_Gaull...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France	2021-11-14
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	http://www.belfastairport.com/	https://en.wikipedia.org/wiki/Belfast_Internat...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	http://www.gva.ch/	https://en.wikipedia.org/wiki/Geneva_Cointrin_...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz	2021-11-14

1800 rows × 58 columns

df_craft.to_csv(r'Flights_Craft.csv')

# Okay, so there are 362 blank departure airport calls. That's just fine.

df.isna().sum()

Unnamed: 0               0
firstSeen                0
lastSeen                 0
icao24                   0
callsign                 0
estDepartureAirport    362
estArrivalAirport        0
dtype: int64

aircraft["407177"]
# Calling an aircraft from the list, just to see if it shows up

	icao24	registration	typecode	serialnumber	model	operator	operatoricao	owner
144903	407177	G-JZBJ	B738
418100	407177

So I've determined that I can use the callsign to reference the aircraft model!

Some of these aircraft don't have an origin. What are they?

plane = aircraft[[dfCAC['callsign']]]
plane

	icao24	registration	typecode	serialnumber	model	operator	operatoricao	owner

Aircraft Database https://opensky-network.org/datasets/metadata/

# RuntimeError: This method requires authentication.
https://opensky-network.org/datasets/metadata/
flight = opensky.history(
    "2017-02-05",
    # stop is implicit, i.e. stop="2017-02-06"
    callsign="EZY158T",
    return_flight=True
)

for col in dfCAC.columns:
    print(col)

firstSeen
lastSeen
icao24
callsign
estDepartureAirport
estArrivalAirport
registration
manufacturericao
manufacturername
model
typecode
serialnumber
linenumber
icaoaircrafttype
operator
operatorcallsign
operatoricao
operatoriata
owner
testreg
registered
reguntil
status
built
firstflightdate
seatconfiguration
engines
modes
adsb
acars
notes
categoryDescription
day
id_x
ident
type
name_x
latitude_deg
longitude_deg
elevation_ft
continent_x
iso_country
iso_region
municipality
scheduled_service
gps_code
iata_code
local_code
home_link
wikipedia_link_x
keywords_x
id_y
code
name_y
continent_y
wikipedia_link_y
keywords_y
date
destlat
destlong
date2

from traffic.data import opensky

# Setting up the start and end times for the retrieval
# This one is the pre-crisis day
pre_day = "2021-10-20"

# # This one is the post-crisis day
# post_day = "2020-04-07"

# This bounding box covers Western Europe (4 major airports)
# lon0, lat0, lon1, lat1
bounds = [-8, 57., 0., 55.]

pre_data = opensky.history(
    start=pre_day,
    bounds=bounds,
    other_params=" and onground=false "
)

# post_data = opensky.history(
#     start=post_day,
#     bounds=bounds,
#     other_params=" and onground=false "
# )

# # Saving data (optional)

# pre_data.to_pickle("2020-10-20_extended_muac.pkl")
# post_data.to_pickle("2020-04-07_extended_muac.pkl")

from pathlib import Path

flightlist = pd.concat(
    pd.read_csv(file, parse_dates=["firstSeen", "lastSeen", "day"])
    for file in Path().glob("Flights_Craft.csv")
)

dfCAC['name_y'].value_counts()

United Kingdom          918
Namibia                 362
Ireland                  97
Netherlands              89
Spain                    78
Germany                  43
France                   27
Portugal                 23
Poland                   20
Jersey                   17
United Arab Emirates     16
Denmark                  14
Italy                    11
Switzerland              11
Greece                   11
Cyprus                   10
United States             8
Sweden                    6
Belgium                   4
Hungary                   4
Saudi Arabia              3
Slovenia                  3
Czech Republic            2
Luxembourg                2
Russia                    2
Malta                     2
Thailand                  2
Turkey                    2
Japan                     2
Australia                 1
South Korea               1
Morocco                   1
Iceland                   1
Austria                   1
Croatia                   1
Bulgaria                  1
Guinea-Bissau             1
Bangladesh                1
Isle of Man               1
Malaysia                  1
Name: name_y, dtype: int64

df_craft['estDepartureAirport'].value_counts()

EGLL    193
EGKK    104
EIDW     96
EHAM     89
EGAA     81
       ... 
BIKF      1
LOWW      1
EDDH      1
LEMD      1
WMKK      1
Name: estDepartureAirport, Length: 120, dtype: int64

opensky.api_tracks(dfCAC.icao24)

---------------------------------------------------------------------------
HTTPError                                 Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/3006333080.py in <module>
----> 1 opensky.api_tracks(dfCAC.icao24)

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/traffic/data/adsb/opensky.py in api_tracks(self, icao24, time)
    284             f"?icao24={icao24}&time={time}"
    285         )
--> 286         c.raise_for_status()
    287         json = c.json()
    288 

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/requests/models.py in raise_for_status(self)
    951 
    952         if http_error_msg:
--> 953             raise HTTPError(http_error_msg, response=self)
    954 
    955     def close(self):

HTTPError: 404 Client Error:  for url: https://opensky-network.org/api/tracks/?icao24=0%20%20%20%20%20%20%20407567%0A1%20%20%20%20%20%20%20407177%0A2%20%20%20%20%20%20%204063de%0A3%20%20%20%20%20%20%20400dc2%0A4%20%20%20%20%20%20%204ca61d%0A%20%20%20%20%20%20%20%20%20...%20%20%0A1795%20%20%20%20406b5a%0A1796%20%20%20%20406b91%0A1797%20%20%20%2040780e%0A1798%20%20%20%204074b2%0A1799%20%20%20%204ac92c%0AName:%20icao24,%20Length:%201800,%20dtype:%20object&time=0

airports_subset = [
    # Europe
    ["LFPG", "EGLL", "EHAM", "EDDF", "LEMD", "LIRF", "LSZH", "UUEE", "EGKK", "EIDW", "EGAA"],
    # Eastern Asia
    ["VHHH", "RJBB", "RJTT", "RKSI", "RCTP", "RPLL"],
    # Asia (other)
    ["YSSY", "YMML", "OMDB", "VABB", "VIDP", "WSSS"],
    # Americas
    ["CYYZ", "KSFO", "KLAX", "KATL", "KJFK", "SBGR"],
]

data = pd.concat(
    (
        dfCAC.query(f'estDepartureAirport == "{airport}"')
        # count the number of departing aircraft per day
        .groupby("day")
        .agg(dict(callsign="count"))
        # label the current chunk with the name of the airport
        .rename(columns=dict(callsign=airport))
        # iterate on all airports in the list hereabove
        for airport in sum(airports_subset, [])
    ),
    axis=1,
)

chart = alt.Chart(
    data.reset_index()
    # prepare data for altair
    .melt("day", var_name="airport", value_name="count")
    # include the name of the city associated with the airport code
    .merge(
        airports.data[["icao", "municipality"]],
        left_on="airport",
        right_on="icao",
        how="left",
    )[["day", "airport", "count", "municipality"]]
    # rename this feature 'city'
    .rename(columns=dict(municipality="city"))
)


def full_chart(source, subset, subset_name):

    # We have many airports, only pick a subset
    chart = source.transform_filter(
        alt.FieldOneOfPredicate(field="airport", oneOf=subset)
    )

    # When we come close to a line, highlight it
    highlight = alt.selection(
        type="single", nearest=True, on="mouseover", fields=["airport"]
    )

    # The scatter plot
    points = (
        chart.mark_point()
        .encode(
            x="day",
            y=alt.Y("count", title="# of departing flights"),
            color=alt.Color("airport", legend=alt.Legend(title=subset_name)),
            # add some legend next to  point
            tooltip=["day", "airport", "city", "count"],
            # not too noisy please
            opacity=alt.value(0.5),
        )
        .add_selection(highlight)
    )

    # The trend plot
    lines = (
        chart.mark_line()
        .encode(
            x="day",
            y="count",
            color="airport",
            size=alt.condition(~highlight, alt.value(1), alt.value(3)),
        )
        # the cloud is a bit messy, draw a trend through it
        .transform_loess("day", "count", groupby=["airport"], bandwidth=0.2)
    )

    return lines + points


# Concatenate several plots
result = alt.vconcat(
    *[
        full_chart(chart, airport_, subset_name).properties(width=600, height=150)
        for subset_name, airport_ in zip(
            [
                "European airports",
                "East-Asian airports",
                "Asian/Australian airports",
                "American airports",
            ],
            airports_subset,
        )
    ]
).resolve_scale(color="independent")

result

dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date	destlat	destlong
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17	55.871899	-4.43306
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17	55.871899	-4.43306
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17	55.871899	-4.43306
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France	2021-11-14	55.871899	-4.43306
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz	2021-11-14	55.871899	-4.43306

1800 rows × 60 columns

val = dfCAC.groupby(['date']).size()
val

date
2021-10-17    45
2021-10-18    62
2021-10-19    53
2021-10-20    59
2021-10-21    57
2021-10-22    72
2021-10-23    49
2021-10-24    62
2021-10-25    61
2021-10-26    51
2021-10-27    55
2021-10-28    53
2021-10-29    66
2021-10-30    50
2021-10-31    83
2021-11-01    85
2021-11-02    98
2021-11-03    78
2021-11-04    82
2021-11-05    73
2021-11-06    46
2021-11-07    58
2021-11-08    66
2021-11-09    65
2021-11-10    67
2021-11-11    66
2021-11-12    64
2021-11-13    57
2021-11-14    17
dtype: int64

import plotly.express as px
df = px.data.gapminder().query("continent == 'Oceania'")
fig = px.line(df, x='year', y='lifeExp', color='country', symbol="country")
fig.show()

for col in dfCAC.columns:
    print(col)

firstSeen
lastSeen
icao24
callsign
estDepartureAirport
estArrivalAirport
registration
manufacturericao
manufacturername
model
typecode
serialnumber
linenumber
icaoaircrafttype
operator
operatorcallsign
operatoricao
operatoriata
owner
testreg
registered
reguntil
status
built
firstflightdate
seatconfiguration
engines
modes
adsb
acars
notes
categoryDescription
day
id_x
ident
type
name_x
latitude_deg
longitude_deg
elevation_ft
continent_x
iso_country
iso_region
municipality
scheduled_service
gps_code
iata_code
local_code
home_link
wikipedia_link_x
keywords_x
id_y
code
name_y
continent_y
wikipedia_link_y
keywords_y
date
destlat
destlong
date2

%matplotlib inline
import matplotlib.pyplot as plt
sns.set()  # use Seaborn styles

dfCAC.pivot_table('icao24', index='date', 
                  columns='estDepartureAirport', aggfunc={'estDepartureAirport':len}).plot()
plt.ylabel('Flights per Airport by Date');

my_pivot = dfCAC.pivot_table(index = 'date', 
                          columns = 'estDepartureAirport', 
                          fill_value = 0, 
                          aggfunc={'estDepartureAirport':len})['estDepartureAirport']
my_pivot.plot.line()
plt.tight_layout()
plt.show()

# dt = dfCAC['date'].value_counts().sort_index()
# date = dfCAC['date']
# import plotly.express as px

# df = px.data.stocks()
# fig = px.line(x=date, y=dt)
# fig.show()

dt = dfCAC.groupby(['date']).size()
dt.plot.line()
#alternative  
#s = df.groupby('date').size()

<AxesSubplot:xlabel='date'>

dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date	destlat	destlong
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17	55.871899	-4.43306
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17	55.871899	-4.43306
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17	55.871899	-4.43306
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	LON, Crawley, Charlwood	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	PAR, Aéroport Roissy-Charles de Gaulle, Roissy...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France	2021-11-14	55.871899	-4.43306
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	Aldergrove, RAF Aldergrove	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	NaN	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz	2021-11-14	55.871899	-4.43306

1800 rows × 60 columns

dfCAC['date2'] = dfCAC['date'].dt.strftime('%m/%d')

# df['DOB1'] = df['DOB'].dt.strftime('%m/%d/%Y')

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2641908597.py in <module>
----> 1 dfCAC['date2'] = dfCAC['date'].dt.strftime('%m/%d')
      2 
      3 # df['DOB1'] = df['DOB'].dt.strftime('%m/%d/%Y')

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/generic.py in __getattr__(self, name)
   5485         ):
   5486             return self[name]
-> 5487         return object.__getattribute__(self, name)
   5488 
   5489     def __setattr__(self, name: str, value) -> None:

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/accessor.py in __get__(self, obj, cls)
    179             # we're accessing the attribute of the class, i.e., Dataset.geo
    180             return self._accessor
--> 181         accessor_obj = self._accessor(obj)
    182         # Replace the property with the accessor object. Inspired by:
    183         # https://www.pydanny.com/cached-property.html

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/indexes/accessors.py in __new__(cls, data)
    504             return PeriodProperties(data, orig)
    505 
--> 506         raise AttributeError("Can only use .dt accessor with datetimelike values")

AttributeError: Can only use .dt accessor with datetimelike values

# Checking my data types - it looks like Tract Rate is an object. 

dfCAC.dtypes

firstSeen                           object
lastSeen               datetime64[ns, UTC]
icao24                              object
callsign                            object
estDepartureAirport                 object
estArrivalAirport                   object
registration                        object
manufacturericao                    object
manufacturername                    object
model                               object
typecode                            object
serialnumber                        object
linenumber                          object
icaoaircrafttype                    object
operator                            object
operatorcallsign                    object
operatoricao                        object
operatoriata                        object
owner                               object
testreg                             object
registered                          object
reguntil                            object
status                             float64
built                               object
firstflightdate                     object
seatconfiguration                  float64
engines                             object
modes                               object
adsb                                object
acars                               object
notes                              float64
categoryDescription                 object
day                                  int64
id_x                               float64
ident                               object
type                                object
name_x                              object
latitude_deg                       float64
longitude_deg                      float64
elevation_ft                       float64
continent_x                         object
iso_country                         object
iso_region                          object
municipality                        object
scheduled_service                   object
gps_code                            object
iata_code                           object
local_code                          object
home_link                           object
wikipedia_link_x                    object
keywords_x                          object
id_y                                 int64
code                                object
name_y                              object
continent_y                         object
wikipedia_link_y                    object
keywords_y                          object
date                                object
destlat                            float64
destlong                           float64
dtype: object

# Let's convert from object to numeric

dfCAC['Tract Rate'] = pd.to_numeric(df['Tract Rate'], errors='coerce')

dfCAC["date2"] = pd.to_datetime(dfCAC["date"]).dt.strftime("%Y%m%d")
print( dfCAC )

                      firstSeen                  lastSeen  icao24 callsign  \
0     2021-10-17 09:39:17+00:00 2021-10-17 12:45:24+00:00  407567  EZY96EM   
1     2021-10-17 10:27:12+00:00 2021-10-17 13:19:21+00:00  407177   EXS8HQ   
2     2021-10-17 12:23:38+00:00 2021-10-17 13:22:08+00:00  4063de    SHT6R   
3     2021-10-17 12:46:14+00:00 2021-10-17 13:35:59+00:00  400dc2    GMA03   
4     2021-10-17 13:01:09+00:00 2021-10-17 13:38:37+00:00  4ca61d  RYR5774   
...                         ...                       ...     ...      ...   
1795  2021-11-14 10:14:18+00:00 2021-11-14 11:10:56+00:00  406b5a  SHT2512   
1796  2021-11-14 09:48:32+00:00 2021-11-14 11:14:57+00:00  406b91  EZY84QK   
1797  2021-11-14 10:30:40+00:00 2021-11-14 11:23:34+00:00  40780e    SHT6T   
1798  2021-11-14 11:10:51+00:00 2021-11-14 11:38:50+00:00  4074b2  EZY576Z   
1799  2021-11-14 09:43:52+00:00 2021-11-14 11:44:11+00:00  4ac92c     JET7   

     estDepartureAirport estArrivalAirport registration manufacturericao  \
0                   LEMG              EGPF          NaN              NaN   
1                   LEAL              EGPF          NaN              NaN   
2                   EGLL              EGPF       G-EUYJ           AIRBUS   
3                    NaN              EGPF       G-SASC         RAYTHEON   
4                   EIDW              EGPF       EI-DWP           BOEING   
...                  ...               ...          ...              ...   
1795                EGKK              EGPF       G-GATK           AIRBUS   
1796                LFPG              EGPF       G-EZWY           AIRBUS   
1797                EGLL              EGPF       G-NEOY              NaN   
1798                EGAA              EGPF          NaN              NaN   
1799                LSGG              EGPF       SE-RIL           CESSNA   

               manufacturername                      model  ...    id_y code  \
0                           NaN                        NaN  ...  302684   ES   
1                           NaN                        NaN  ...  302684   ES   
2                    Airbus Sas            AIRBUS A320-232  ...  302688   GB   
3     Raytheon Aircraft Company  BEECH B200C Super Kingair  ...  302591  NaN   
4            The Boeing Company             BOEING 737-8AS  ...  302694   IE   
...                         ...                        ...  ...     ...  ...   
1795                 Airbus Sas            AIRBUS A320-232  ...  302688   GB   
1796                 Airbus Sas            AIRBUS A320-214  ...  302687   FR   
1797                        NaN                        NaN  ...  302688   GB   
1798                        NaN                        NaN  ...  302688   GB   
1799                     Cessna               Citation XLS  ...  302679   CH   

              name_y continent_y  \
0              Spain          EU   
1              Spain          EU   
2     United Kingdom          EU   
3            Namibia          AF   
4            Ireland          EU   
...              ...         ...   
1795  United Kingdom          EU   
1796          France          EU   
1797  United Kingdom          EU   
1798  United Kingdom          EU   
1799     Switzerland          EU   

                                  wikipedia_link_y  \
0              https://en.wikipedia.org/wiki/Spain   
1              https://en.wikipedia.org/wiki/Spain   
2     https://en.wikipedia.org/wiki/United_Kingdom   
3            https://en.wikipedia.org/wiki/Namibia   
4            https://en.wikipedia.org/wiki/Ireland   
...                                            ...   
1795  https://en.wikipedia.org/wiki/United_Kingdom   
1796          https://en.wikipedia.org/wiki/France   
1797  https://en.wikipedia.org/wiki/United_Kingdom   
1798  https://en.wikipedia.org/wiki/United_Kingdom   
1799     https://en.wikipedia.org/wiki/Switzerland   

                                        keywords_y        date    destlat  \
0                            Aeropuertos de España  2021-10-17  55.871899   
1                            Aeropuertos de España  2021-10-17  55.871899   
2                                    Great Britain  2021-10-17  55.871899   
3                                              NaN  2021-10-17  55.871899   
4                                             Eire  2021-10-17  55.871899   
...                                            ...         ...        ...   
1795                                 Great Britain  2021-11-14  55.871899   
1796                           Aéroports de France  2021-11-14  55.871899   
1797                                 Great Britain  2021-11-14  55.871899   
1798                                 Great Britain  2021-11-14  55.871899   
1799  Aéroports de la Suisse,Flughäfen der Schweiz  2021-11-14  55.871899   

     destlong     date2  
0    -4.43306  20211017  
1    -4.43306  20211017  
2    -4.43306  20211017  
3    -4.43306  20211017  
4    -4.43306  20211017  
...       ...       ...  
1795 -4.43306  20211114  
1796 -4.43306  20211114  
1797 -4.43306  20211114  
1798 -4.43306  20211114  
1799 -4.43306  20211114  

[1800 rows x 61 columns]

dfCAC['date2'] = dfCAC['date'].astype('str') 

dfCAC['date2'] = dfCAC['date2'].str.slice(5)

dfCAC

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date	destlat	destlong	date2
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306	10-17
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306	10-17
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17	55.871899	-4.43306	10-17
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17	55.871899	-4.43306	10-17
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17	55.871899	-4.43306	10-17
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1795	2021-11-14 10:14:18+00:00	2021-11-14 11:10:56+00:00	406b5a	SHT2512	EGKK	EGPF	G-GATK	AIRBUS	Airbus Sas	AIRBUS A320-232	...	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306	11-14
1796	2021-11-14 09:48:32+00:00	2021-11-14 11:14:57+00:00	406b91	EZY84QK	LFPG	EGPF	G-EZWY	AIRBUS	Airbus Sas	AIRBUS A320-214	...	302687	FR	France	EU	https://en.wikipedia.org/wiki/France	Aéroports de France	2021-11-14	55.871899	-4.43306	11-14
1797	2021-11-14 10:30:40+00:00	2021-11-14 11:23:34+00:00	40780e	SHT6T	EGLL	EGPF	G-NEOY	NaN	NaN	NaN	...	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306	11-14
1798	2021-11-14 11:10:51+00:00	2021-11-14 11:38:50+00:00	4074b2	EZY576Z	EGAA	EGPF	NaN	NaN	NaN	NaN	...	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-11-14	55.871899	-4.43306	11-14
1799	2021-11-14 09:43:52+00:00	2021-11-14 11:44:11+00:00	4ac92c	JET7	LSGG	EGPF	SE-RIL	CESSNA	Cessna	Citation XLS	...	302679	CH	Switzerland	EU	https://en.wikipedia.org/wiki/Switzerland	Aéroports de la Suisse,Flughäfen der Schweiz	2021-11-14	55.871899	-4.43306	11-14

1800 rows × 61 columns

dfCAC.head(5)

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date	destlat	destlong	date2
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306	10-17
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17	55.871899	-4.43306	10-17
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17	55.871899	-4.43306	10-17
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17	55.871899	-4.43306	10-17
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17	55.871899	-4.43306	10-17

5 rows × 61 columns

dfCAC.types()

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/154117220.py in <module>
----> 1 dfCAC.types()

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/generic.py in __getattr__(self, name)
   5485         ):
   5486             return self[name]
-> 5487         return object.__getattribute__(self, name)
   5488 
   5489     def __setattr__(self, name: str, value) -> None:

AttributeError: 'DataFrame' object has no attribute 'types'

airports_subset = [
    # Europe
    ["LFPG", "EGLL", "EHAM", "EDDF", "LEMD", "LIRF", "LSZH", "UUEE", "EGKK", "EIDW", "EGAA"],
    # Eastern Asia
    ["VHHH", "RJBB", "RJTT", "RKSI", "RCTP", "RPLL"],
    # Asia (other)
    ["YSSY", "YMML", "OMDB", "VABB", "VIDP", "WSSS"],
    # Americas
    ["CYYZ", "KSFO", "KLAX", "KATL", "KJFK", "SBGR"],
]

data = pd.concat(
    (
        dfCAC.query(f'estDepartureAirport == "{airport}"')
        # count the number of departing aircraft per day
        .groupby("date2")
        .agg(dict(callsign="count"))
        # label the current chunk with the name of the airport
        .rename(columns=dict(callsign=airport))
        # iterate on all airports in the list hereabove
        for airport in sum(airports_subset, [])
    ),
    axis=1,
)

chart = alt.Chart(
    data.reset_index()
    # prepare data for altair
    .melt("date2", var_name="airport", value_name="count")
    # include the name of the city associated with the airport code
    .merge(
        airports.data[["icao", "municipality"]],
        left_on="airport",
        right_on="icao",
        how="left",
    )[["date2", "airport", "count", "municipality"]]
    # rename this feature 'city'
    .rename(columns=dict(municipality="city"))
)


def full_chart(source, subset, subset_name):

    # We have many airports, only pick a subset
    chart = source.transform_filter(
        alt.FieldOneOfPredicate(field="airport", oneOf=subset)
    )

    # When we come close to a line, highlight it
    highlight = alt.selection(
        type="single", nearest=True, on="mouseover", fields=["airport"]
    )

    # The scatter plot
    points = (
        chart.mark_point()
        .encode(
            x="date2",
            y=alt.Y("count", title="# of departing flights"),
            color=alt.Color("airport", legend=alt.Legend(title=subset_name)),
            # add some legend next to  point
            tooltip=["date2", "airport", "city", "count"],
            # not too noisy please
            opacity=alt.value(0.5),
        )
        .add_selection(highlight)
    )

    # The trend plot
    lines = (
        chart.mark_line()
        .encode(
            x="date2",
            y="count",
            color="airport",
            size=alt.condition(~highlight, alt.value(1), alt.value(3)),
        )
        # the cloud is a bit messy, draw a trend through it
        .transform_loess("date2", "count", groupby=["airport"], bandwidth=0.2)
    )

    return lines + points


# Concatenate several plots
result = alt.vconcat(
    *[
        full_chart(chart, airport_, subset_name).properties(width=600, height=150)
        for subset_name, airport_ in zip(
            [
                "European airports",
                "East-Asian airports",
                "Asian/Australian airports",
                "American airports",
            ],
            airports_subset,
        )
    ]
).resolve_scale(color="independent")

result

pre_data

from traffic.data import eurofirs
from traffic.data.samples import switzerland

df = opensky.extended(
    switzerland.start_time,
    switzerland.end_time,
    bounds=eurofirs['LSAS']
)

enriched_ch = (
    switzerland
    .filter()
    .query_ehs(df)
    .resample('1s')
    .eval(desc='', max_workers=4)
)

WARNING:root:No data on Impala for flight SAA261.
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WARNING:root:No data on Impala for flight TUI32F.
WARNING:root:No data on Impala for flight TUI5DH.
WARNING:root:No data on Impala for flight TUI7WC.
WARNING:root:No data on Impala for flight TUI21M.
WARNING:root:No data on Impala for flight TUI6515.
WARNING:root:No data on Impala for flight TUI6503.
WARNING:root:No data on Impala for flight TUI9XE.
WARNING:root:No data on Impala for flight TUI2619.
WARNING:root:No data on Impala for flight TUI58M.
WARNING:root:No data on Impala for flight BAW54RT.
WARNING:root:No data on Impala for flight BMW54.
WARNING:root:No data on Impala for flight EWG230.
WARNING:root:No data on Impala for flight ARZ8336.
WARNING:root:No data on Impala for flight EWG2UH.
WARNING:root:No data on Impala for flight EWG3ZA.
WARNING:root:No data on Impala for flight EWG8EW.
WARNING:root:No data on Impala for flight EWG91P.
WARNING:root:No data on Impala for flight EWG15A.
WARNING:root:No data on Impala for flight EWG7VC.
WARNING:root:No data on Impala for flight EWG2YC.
WARNING:root:No data on Impala for flight EWG8RG.
WARNING:root:No data on Impala for flight EWG9BL.
WARNING:root:No data on Impala for flight EWG2EJ.
WARNING:root:No data on Impala for flight EWG3GZ.
WARNING:root:No data on Impala for flight TUI1TK.
WARNING:root:No data on Impala for flight EWG6KR.
WARNING:root:No data on Impala for flight EWG2VR.
WARNING:root:No data on Impala for flight EWG5TR.
WARNING:root:No data on Impala for flight EWG7GL.
WARNING:root:No data on Impala for flight EWG8WT.
WARNING:root:No data on Impala for flight CFG7MA.
WARNING:root:No data on Impala for flight CFG4HF.
WARNING:root:No data on Impala for flight CFG8KA.
WARNING:root:No data on Impala for flight CFG2LV.
WARNING:root:No data on Impala for flight CFG5HC.
WARNING:root:No data on Impala for flight CFG5KT.
WARNING:root:No data on Impala for flight CFG8ME.
WARNING:root:No data on Impala for flight CFG293.
WARNING:root:No data on Impala for flight EWG4EU.
WARNING:root:No data on Impala for flight DLH572.
WARNING:root:No data on Impala for flight EWG8HZ.
WARNING:root:No data on Impala for flight EWG9580.
WARNING:root:No data on Impala for flight EWG9581.
WARNING:root:No data on Impala for flight DLH6RW.
WARNING:root:No data on Impala for flight DLH6KA.
WARNING:root:No data on Impala for flight DLH1424.
WARNING:root:No data on Impala for flight EWG3EW.
WARNING:root:No data on Impala for flight EWG4Z.
WARNING:root:No data on Impala for flight EWG82W.
WARNING:root:No data on Impala for flight EWG6VU.
WARNING:root:No data on Impala for flight GWI6906.
WARNING:root:No data on Impala for flight EWG3RH.
WARNING:root:No data on Impala for flight EWG6CV.
WARNING:root:No data on Impala for flight EWG3LR.
WARNING:root:No data on Impala for flight EWG7RZ.
WARNING:root:No data on Impala for flight EWG7BP.
WARNING:root:No data on Impala for flight EWG7521.
WARNING:root:No data on Impala for flight EWG8MF.
WARNING:root:No data on Impala for flight EWG38A.
WARNING:root:No data on Impala for flight EWG8KK.
WARNING:root:No data on Impala for flight EWG3NR.
WARNING:root:No data on Impala for flight EWG9GK.
WARNING:root:No data on Impala for flight AHO797W.
WARNING:root:No data on Impala for flight GMI12HJ.
WARNING:root:No data on Impala for flight EWG582.
WARNING:root:No data on Impala for flight EWG583.
WARNING:root:No data on Impala for flight EWG9RC.
WARNING:root:No data on Impala for flight EWG5938.
WARNING:root:No data on Impala for flight EWG1NY.
WARNING:root:No data on Impala for flight EWG391.
WARNING:root:No data on Impala for flight EWG31J.
WARNING:root:No data on Impala for flight EWG5EB.
WARNING:root:No data on Impala for flight EWG3MG.
WARNING:root:No data on Impala for flight EWG591.
WARNING:root:No data on Impala for flight AHO518U.
WARNING:root:No data on Impala for flight TUI48G.
WARNING:root:No data on Impala for flight CFG848.
WARNING:root:No data on Impala for flight CFG849.
WARNING:root:No data on Impala for flight CFG875.
WARNING:root:No data on Impala for flight DLH88W.
WARNING:root:No data on Impala for flight DLH35X.
WARNING:root:No data on Impala for flight CFG8AC.
WARNING:root:No data on Impala for flight CFG1DY.
WARNING:root:No data on Impala for flight CFG9KE.
WARNING:root:No data on Impala for flight DLH44C.
WARNING:root:No data on Impala for flight DLH07X.
WARNING:root:No data on Impala for flight DLH91H.
WARNING:root:No data on Impala for flight DLH61U.
WARNING:root:No data on Impala for flight DLH97E.
WARNING:root:No data on Impala for flight DLH51J.
WARNING:root:No data on Impala for flight DLH53P.
WARNING:root:No data on Impala for flight DLH59H.
WARNING:root:No data on Impala for flight DLH77C.
WARNING:root:No data on Impala for flight DLH62Y.
WARNING:root:No data on Impala for flight DLH21P.
WARNING:root:No data on Impala for flight DLH4RW.
WARNING:root:No data on Impala for flight DLH9FY.
WARNING:root:No data on Impala for flight DLH87Y.
WARNING:root:No data on Impala for flight DLH17N.
WARNING:root:No data on Impala for flight DLH2VV.
WARNING:root:No data on Impala for flight DLH37N.
WARNING:root:No data on Impala for flight DLH88P.
WARNING:root:No data on Impala for flight EWG6K.
WARNING:root:No data on Impala for flight DLH8RM.
WARNING:root:No data on Impala for flight EWG9PA.
WARNING:root:No data on Impala for flight EWG9UR.
WARNING:root:No data on Impala for flight DLH18X.
WARNING:root:No data on Impala for flight DLH72T.
WARNING:root:No data on Impala for flight EWG7AL.
WARNING:root:No data on Impala for flight EWG520.
WARNING:root:No data on Impala for flight EWG521.
WARNING:root:No data on Impala for flight DLH52X.
WARNING:root:No data on Impala for flight DLH55K.
WARNING:root:No data on Impala for flight EWG580.
WARNING:root:No data on Impala for flight EWG581.
WARNING:root:No data on Impala for flight EWG599.
WARNING:root:No data on Impala for flight DLH99P.
WARNING:root:No data on Impala for flight DLH03Y.
WARNING:root:No data on Impala for flight DLH05A.
WARNING:root:No data on Impala for flight DLH08X.
WARNING:root:No data on Impala for flight DLH68W.
WARNING:root:No data on Impala for flight DLH01M.
WARNING:root:No data on Impala for flight DLH02A.
WARNING:root:No data on Impala for flight DLH37F.
WARNING:root:No data on Impala for flight DLH3CM.
WARNING:root:No data on Impala for flight DLH19P.
WARNING:root:No data on Impala for flight DLH45N.
WARNING:root:No data on Impala for flight DLH75U.
WARNING:root:No data on Impala for flight DLH55E.
WARNING:root:No data on Impala for flight DLH54M.
WARNING:root:No data on Impala for flight DLH1322.
WARNING:root:No data on Impala for flight DLH1323.
WARNING:root:No data on Impala for flight DLH99X.
WARNING:root:No data on Impala for flight DLH42K.
WARNING:root:No data on Impala for flight DLH1158.
WARNING:root:No data on Impala for flight DLH1159.
WARNING:root:No data on Impala for flight DLH05E.
WARNING:root:No data on Impala for flight DLH6UV.
WARNING:root:No data on Impala for flight DLH85N.
WARNING:root:No data on Impala for flight DLH54C.
WARNING:root:No data on Impala for flight DLH2UX.
WARNING:root:No data on Impala for flight DLH1152.
WARNING:root:No data on Impala for flight DLH1153.
WARNING:root:No data on Impala for flight DLH44M.
WARNING:root:No data on Impala for flight DLH1157.
WARNING:root:No data on Impala for flight DLH336.
WARNING:root:No data on Impala for flight DLH77P.
WARNING:root:No data on Impala for flight DLH9CJ.
WARNING:root:No data on Impala for flight DLH64U.
WARNING:root:No data on Impala for flight DLH98F.
WARNING:root:No data on Impala for flight DLH7MM.
WARNING:root:No data on Impala for flight DLH9HP.
WARNING:root:No data on Impala for flight DLH5UW.
WARNING:root:No data on Impala for flight DLH6KK.
WARNING:root:No data on Impala for flight DLH3WJ.
WARNING:root:No data on Impala for flight DLH39X.
WARNING:root:No data on Impala for flight DLH08Y.
WARNING:root:No data on Impala for flight DLH1316.
WARNING:root:No data on Impala for flight DLH28Y.
WARNING:root:No data on Impala for flight DLH52T.
WARNING:root:No data on Impala for flight DLH06K.
WARNING:root:No data on Impala for flight EWG1YF.
WARNING:root:No data on Impala for flight DLH47E.
WARNING:root:No data on Impala for flight EWG6GR.
WARNING:root:No data on Impala for flight DLH8CU.
WARNING:root:No data on Impala for flight DLH49P.
WARNING:root:No data on Impala for flight DLH54N.
WARNING:root:No data on Impala for flight EWG3VU.
WARNING:root:No data on Impala for flight EWG7XA.
WARNING:root:No data on Impala for flight EWG1VT.
WARNING:root:No data on Impala for flight GEC8269.
WARNING:root:No data on Impala for flight EWG5XC.
WARNING:root:No data on Impala for flight BCS6823.
WARNING:root:No data on Impala for flight BCS6824.
WARNING:root:No data on Impala for flight EFD3P.
WARNING:root:No data on Impala for flight HHN20B.
WARNING:root:No data on Impala for flight DCS705.
WARNING:root:No data on Impala for flight DIMAH.
WARNING:root:No data on Impala for flight XGO2MV.
WARNING:root:No data on Impala for flight AHO726M.
WARNING:root:No data on Impala for flight BAW559.
WARNING:root:No data on Impala for flight ATL5B.
WARNING:root:No data on Impala for flight BAW64CF.
WARNING:root:No data on Impala for flight BAW633.
WARNING:root:No data on Impala for flight BAW82GR.
WARNING:root:No data on Impala for flight BAW59GT.
WARNING:root:No data on Impala for flight BAW66GA.
WARNING:root:No data on Impala for flight CLJ6325.
WARNING:root:No data on Impala for flight TOM6WG.
WARNING:root:No data on Impala for flight TCX3HF.
WARNING:root:No data on Impala for flight TCX1124.
WARNING:root:No data on Impala for flight TCX7WG.
WARNING:root:No data on Impala for flight BAW598D.
WARNING:root:No data on Impala for flight BAW61BA.
WARNING:root:No data on Impala for flight BAW2591.
WARNING:root:No data on Impala for flight BAW639.
WARNING:root:No data on Impala for flight BAW599.
WARNING:root:No data on Impala for flight BAW631.
WARNING:root:No data on Impala for flight BAW658.
WARNING:root:No data on Impala for flight BAW659.
WARNING:root:No data on Impala for flight EXS36K.
WARNING:root:No data on Impala for flight EXS68L.
WARNING:root:No data on Impala for flight BAW48G.
WARNING:root:No data on Impala for flight BAW585E.
WARNING:root:No data on Impala for flight BAW84ZV.
WARNING:root:No data on Impala for flight BAW881V.
WARNING:root:No data on Impala for flight BAW2649.
WARNING:root:No data on Impala for flight BAW65PL.
WARNING:root:No data on Impala for flight BAW3RP.
WARNING:root:No data on Impala for flight BAW15PZ.
WARNING:root:No data on Impala for flight BAW579V.
WARNING:root:No data on Impala for flight BAW555.
WARNING:root:No data on Impala for flight BAW609.
WARNING:root:No data on Impala for flight BAW604.
WARNING:root:No data on Impala for flight BAW605.
WARNING:root:No data on Impala for flight EZY34DV.
WARNING:root:No data on Impala for flight BAW9WZ.
WARNING:root:No data on Impala for flight BAW34BQ.
WARNING:root:No data on Impala for flight BAW557.
WARNING:root:No data on Impala for flight EZY25MR.
WARNING:root:No data on Impala for flight BAW542.
WARNING:root:No data on Impala for flight BAW545.
WARNING:root:No data on Impala for flight EZY79PR.
WARNING:root:No data on Impala for flight EZY96YD.
WARNING:root:No data on Impala for flight EXS69H.
WARNING:root:No data on Impala for flight EXS81J.
WARNING:root:No data on Impala for flight EXS88C.
WARNING:root:No data on Impala for flight EZY59EG.
WARNING:root:No data on Impala for flight EZY36ZH.
WARNING:root:No data on Impala for flight BAW18VT.
WARNING:root:No data on Impala for flight BAW53ZG.
WARNING:root:No data on Impala for flight EZY15PT.
WARNING:root:No data on Impala for flight EZY61LE.
WARNING:root:No data on Impala for flight EZY98XB.
WARNING:root:No data on Impala for flight EZY25AM.
WARNING:root:No data on Impala for flight EZY96HL.
WARNING:root:No data on Impala for flight EZY87YR.
WARNING:root:No data on Impala for flight BAW43LQ.
WARNING:root:No data on Impala for flight BAW544K.
WARNING:root:No data on Impala for flight BAW65TR.
WARNING:root:No data on Impala for flight EZY13QM.
WARNING:root:No data on Impala for flight EZY57JW.
WARNING:root:No data on Impala for flight EZY58WQ.
WARNING:root:No data on Impala for flight GCEYL.
WARNING:root:No data on Impala for flight TOM6LY.
WARNING:root:No data on Impala for flight GRHMS.
WARNING:root:No data on Impala for flight EZY93UQ.
WARNING:root:No data on Impala for flight EZY8072.
WARNING:root:No data on Impala for flight EZY71VB.
WARNING:root:No data on Impala for flight EZY49WH.
WARNING:root:No data on Impala for flight EZY48PA.
WARNING:root:No data on Impala for flight BAW650.
WARNING:root:No data on Impala for flight BAW651.
WARNING:root:No data on Impala for flight BAW256R.
WARNING:root:No data on Impala for flight EZY27XG.
WARNING:root:No data on Impala for flight EZY31CN.
WARNING:root:No data on Impala for flight EZY59UF.
WARNING:root:No data on Impala for flight EZY64GM.
WARNING:root:No data on Impala for flight EZY97FB.
WARNING:root:No data on Impala for flight TOM86V.
WARNING:root:No data on Impala for flight TOM6GK.
WARNING:root:No data on Impala for flight EXS695.
WARNING:root:No data on Impala for flight EXS96H.
WARNING:root:No data on Impala for flight BAW127E.
WARNING:root:No data on Impala for flight BAW71CU.
WARNING:root:No data on Impala for flight TOM6BV.
WARNING:root:No data on Impala for flight EZY17VX.
WARNING:root:No data on Impala for flight EZY72NK.
WARNING:root:No data on Impala for flight EZY51YE.
WARNING:root:No data on Impala for flight EZY56JL.
WARNING:root:No data on Impala for flight TOM736.
WARNING:root:No data on Impala for flight TOM46K.
WARNING:root:No data on Impala for flight TOM1MB.
WARNING:root:No data on Impala for flight EZY72YT.
WARNING:root:No data on Impala for flight EZY8062.
WARNING:root:No data on Impala for flight EZY74DG.
WARNING:root:No data on Impala for flight EZY26KV.
WARNING:root:No data on Impala for flight EZY95KU.
WARNING:root:No data on Impala for flight TOM32T.
WARNING:root:No data on Impala for flight TOM2XE.
WARNING:root:No data on Impala for flight TOM84E.
WARNING:root:No data on Impala for flight TOM9MH.
WARNING:root:No data on Impala for flight TCX7NG.
WARNING:root:No data on Impala for flight EXS33W.
WARNING:root:No data on Impala for flight EZY26PD.
WARNING:root:No data on Impala for flight EZY319P.
WARNING:root:No data on Impala for flight EZY38XB.
WARNING:root:No data on Impala for flight EZY807U.
WARNING:root:No data on Impala for flight BAW842P.
WARNING:root:No data on Impala for flight BAW843R.
WARNING:root:No data on Impala for flight EZY35XQ.
WARNING:root:No data on Impala for flight EZY95HV.
WARNING:root:No data on Impala for flight TCX430.
WARNING:root:No data on Impala for flight TCX108.
WARNING:root:No data on Impala for flight TCX702.
WARNING:root:No data on Impala for flight BAW661.
WARNING:root:No data on Impala for flight TOM5JW.
WARNING:root:No data on Impala for flight BAW3KG.
WARNING:root:No data on Impala for flight BAW2557.
WARNING:root:No data on Impala for flight BAW77PL.
WARNING:root:No data on Impala for flight BAW79PL.
WARNING:root:No data on Impala for flight BAW2677.
WARNING:root:No data on Impala for flight BAW205E.
WARNING:root:No data on Impala for flight BAW58GV.
WARNING:root:No data on Impala for flight BAW50MJ.
WARNING:root:No data on Impala for flight BAW2640.
WARNING:root:No data on Impala for flight TCX1106.
WARNING:root:No data on Impala for flight BAW2641.
WARNING:root:No data on Impala for flight TCX1KU.
WARNING:root:No data on Impala for flight TCX1107.
WARNING:root:No data on Impala for flight TCX114.
WARNING:root:No data on Impala for flight EZY19QP.
WARNING:root:No data on Impala for flight BAW132.
WARNING:root:No data on Impala for flight EZY85PZ.
WARNING:root:No data on Impala for flight EZY54UC.
WARNING:root:No data on Impala for flight EZY49GN.
WARNING:root:No data on Impala for flight EZY63RK.
WARNING:root:No data on Impala for flight TCX1V.
WARNING:root:No data on Impala for flight TCX9FY.
WARNING:root:No data on Impala for flight BAW154.
WARNING:root:No data on Impala for flight IBK2525.
WARNING:root:No data on Impala for flight EXS48P.
WARNING:root:No data on Impala for flight EXS99VN.
WARNING:root:No data on Impala for flight EXS22EF.
WARNING:root:No data on Impala for flight EXS1262.
WARNING:root:No data on Impala for flight EXS12PK.
WARNING:root:No data on Impala for flight EXS61AB.
WARNING:root:No data on Impala for flight EXS64C.
WARNING:root:No data on Impala for flight EXS64W.
WARNING:root:No data on Impala for flight TOM313.
WARNING:root:No data on Impala for flight EZY89KC.
WARNING:root:No data on Impala for flight EZY17ED.
WARNING:root:No data on Impala for flight EZY24UT.
WARNING:root:No data on Impala for flight EZY32TR.
WARNING:root:No data on Impala for flight WZZ6738.
WARNING:root:No data on Impala for flight EZY24DP.
WARNING:root:No data on Impala for flight EZY26UE.
WARNING:root:No data on Impala for flight EXS1678.
WARNING:root:No data on Impala for flight EXS77CK.
WARNING:root:No data on Impala for flight EZY12UH.
WARNING:root:No data on Impala for flight EZY67DE.
WARNING:root:No data on Impala for flight CFE79DW.
WARNING:root:No data on Impala for flight SBI3071.
WARNING:root:No data on Impala for flight VPCSK.
WARNING:root:No data on Impala for flight VPCIG.
WARNING:root:No data on Impala for flight AFL2602.
WARNING:root:No data on Impala for flight AFL2603.
WARNING:root:No data on Impala for flight AFL2500.
WARNING:root:No data on Impala for flight AFL2604.
WARNING:root:No data on Impala for flight AFL2501.
WARNING:root:No data on Impala for flight AFL2620.
WARNING:root:No data on Impala for flight AFL2606.
WARNING:root:No data on Impala for flight PBD878.
WARNING:root:No data on Impala for flight GMI66WA.
WARNING:root:No data on Impala for flight SDM6701.
WARNING:root:No data on Impala for flight EZY12VJ.
WARNING:root:No data on Impala for flight EZY24AX.
WARNING:root:No data on Impala for flight EZY28LB.
WARNING:root:No data on Impala for flight EZY35RV.
WARNING:root:No data on Impala for flight EZY64HB.
WARNING:root:No data on Impala for flight EZY13KH.
WARNING:root:No data on Impala for flight AUA417C.
WARNING:root:No data on Impala for flight FOO1001.
WARNING:root:No data on Impala for flight AUA427.
WARNING:root:No data on Impala for flight EZY12EJ.
WARNING:root:No data on Impala for flight EZY28CD.
WARNING:root:No data on Impala for flight EZY32EN.
WARNING:root:No data on Impala for flight EZY48HB.
WARNING:root:No data on Impala for flight EZY58TR.
WARNING:root:No data on Impala for flight EZY85GE.
WARNING:root:No data on Impala for flight LDM103.
WARNING:root:No data on Impala for flight LDM118.
WARNING:root:No data on Impala for flight LDM71A.
WARNING:root:No data on Impala for flight EZY168Y.
WARNING:root:No data on Impala for flight EZY3891.
WARNING:root:No data on Impala for flight EZY45XA.
WARNING:root:No data on Impala for flight EZY89WP.
WARNING:root:No data on Impala for flight LDM109.
WARNING:root:No data on Impala for flight LDM110.
WARNING:root:No data on Impala for flight EZY68DX.
WARNING:root:No data on Impala for flight EZY23ZB.
WARNING:root:No data on Impala for flight EZY14HN.
WARNING:root:No data on Impala for flight EZY3797.
WARNING:root:No data on Impala for flight EZY39PJ.
WARNING:root:No data on Impala for flight EZY85ZE.
WARNING:root:No data on Impala for flight EZY36CX.
WARNING:root:No data on Impala for flight EZY403R.
WARNING:root:No data on Impala for flight EZY79HE.
WARNING:root:No data on Impala for flight EZY53JP.
WARNING:root:No data on Impala for flight EZY34TM.
WARNING:root:No data on Impala for flight EZY72UF.
WARNING:root:No data on Impala for flight EZY4207.
WARNING:root:No data on Impala for flight EZY47DP.
WARNING:root:No data on Impala for flight EZY79MU.
WARNING:root:No data on Impala for flight AUA415C.
WARNING:root:No data on Impala for flight EZY32RJ.
WARNING:root:No data on Impala for flight EZY95ME.
WARNING:root:No data on Impala for flight EZY63EP.
WARNING:root:No data on Impala for flight AUA414.
WARNING:root:No data on Impala for flight EZY59JC.
WARNING:root:No data on Impala for flight EZY78ZE.
WARNING:root:No data on Impala for flight EZY42RN.
WARNING:root:No data on Impala for flight EZY48QE.
WARNING:root:No data on Impala for flight EWG5889.
WARNING:root:No data on Impala for flight EZY39DR.
WARNING:root:No data on Impala for flight EZY78ED.
WARNING:root:No data on Impala for flight GAC134D.
WARNING:root:No data on Impala for flight EZY168D.
WARNING:root:No data on Impala for flight EZY69ML.
WARNING:root:No data on Impala for flight EZY13XP.
WARNING:root:No data on Impala for flight EZY94XF.
WARNING:root:No data on Impala for flight EZY97QR.
WARNING:root:No data on Impala for flight AUA96LU.
WARNING:root:No data on Impala for flight EZY27NC.
WARNING:root:No data on Impala for flight EZY27JF.
WARNING:root:No data on Impala for flight EZY58YM.
WARNING:root:No data on Impala for flight EZY78CT.
WARNING:root:No data on Impala for flight EWG4YA.
WARNING:root:No data on Impala for flight EWG6808.
WARNING:root:No data on Impala for flight EWG6860.
WARNING:root:No data on Impala for flight EWG9ZX.
WARNING:root:No data on Impala for flight EZY3737.
WARNING:root:No data on Impala for flight EWG6850.
WARNING:root:No data on Impala for flight EZY3738.
WARNING:root:No data on Impala for flight LDM150.
WARNING:root:No data on Impala for flight LDM101.
WARNING:root:No data on Impala for flight LDM151.
WARNING:root:No data on Impala for flight LDM102.
WARNING:root:No data on Impala for flight LDM119.
WARNING:root:No data on Impala for flight EZY539C.
WARNING:root:No data on Impala for flight AAB405.
WARNING:root:No data on Impala for flight LDM120.
WARNING:root:No data on Impala for flight JAF1CP.
WARNING:root:No data on Impala for flight JAF32A.
WARNING:root:No data on Impala for flight JAF14X.
WARNING:root:No data on Impala for flight JAF3HL.
WARNING:root:No data on Impala for flight JAF93K.
WARNING:root:No data on Impala for flight BEL371.
WARNING:root:No data on Impala for flight OOPRM.
WARNING:root:No data on Impala for flight BEL68E.
WARNING:root:No data on Impala for flight BEL6CE.
WARNING:root:No data on Impala for flight BEL3107.
WARNING:root:No data on Impala for flight BEL3108.
WARNING:root:No data on Impala for flight BEL3325.
WARNING:root:No data on Impala for flight BEL3370.
WARNING:root:No data on Impala for flight BEL3885.
WARNING:root:No data on Impala for flight BEL3272.
WARNING:root:No data on Impala for flight BEL3766.
WARNING:root:No data on Impala for flight BEL5FC.
WARNING:root:No data on Impala for flight BEL75Y.
WARNING:root:No data on Impala for flight BEL76F.
WARNING:root:No data on Impala for flight JAF9GL.
WARNING:root:No data on Impala for flight BEL36V.
WARNING:root:No data on Impala for flight BEL14Q.
WARNING:root:No data on Impala for flight BEL9LR.
WARNING:root:No data on Impala for flight BEL3136.
WARNING:root:No data on Impala for flight BEL8NB.
WARNING:root:No data on Impala for flight BEL7MR.
WARNING:root:No data on Impala for flight BEL3577.
WARNING:root:No data on Impala for flight BEL3616.
WARNING:root:No data on Impala for flight BEL54X.
WARNING:root:No data on Impala for flight BEL88F.
WARNING:root:No data on Impala for flight BEL31P.
WARNING:root:No data on Impala for flight BEL9NA.
WARNING:root:No data on Impala for flight BEL10X.
WARNING:root:No data on Impala for flight BEL22N.
WARNING:root:No data on Impala for flight BEL3623.
WARNING:root:No data on Impala for flight BEL5HR.
WARNING:root:No data on Impala for flight BEL81Z.
WARNING:root:No data on Impala for flight BEL3881.
WARNING:root:No data on Impala for flight BEL43D.
WARNING:root:No data on Impala for flight BEL82F.
WARNING:root:No data on Impala for flight BEL3882.
WARNING:root:No data on Impala for flight JAF3924.
WARNING:root:No data on Impala for flight JAF66D.
WARNING:root:No data on Impala for flight JAF38A.
WARNING:root:No data on Impala for flight LZB407.
WARNING:root:No data on Impala for flight LZB408.
WARNING:root:No data on Impala for flight LZB432.
WARNING:root:No data on Impala for flight LZB431.
WARNING:root:No data on Impala for flight LZB851.
WARNING:root:No data on Impala for flight SAS2588.
WARNING:root:No data on Impala for flight SAS775.
WARNING:root:No data on Impala for flight SAS776.
WARNING:root:No data on Impala for flight SAS792.
WARNING:root:No data on Impala for flight SAS791.
WARNING:root:No data on Impala for flight SAS2555.
WARNING:root:No data on Impala for flight DTR635.
WARNING:root:No data on Impala for flight DTR636.
WARNING:root:No data on Impala for flight CSA700.
WARNING:root:No data on Impala for flight CSA701.
WARNING:root:No data on Impala for flight SRR6381.
WARNING:root:No data on Impala for flight AEE4CA.
WARNING:root:No data on Impala for flight AEE615.
WARNING:root:No data on Impala for flight AEE61CG.
WARNING:root:No data on Impala for flight AEE61PG.
WARNING:root:No data on Impala for flight AEE3NC.
WARNING:root:No data on Impala for flight AEE5CD.
WARNING:root:No data on Impala for flight AEE3DW.
WARNING:root:No data on Impala for flight AEE618.
WARNING:root:No data on Impala for flight AEE601.
WARNING:root:No data on Impala for flight AEE2FL.
WARNING:root:No data on Impala for flight AEE6AV.
WARNING:root:No data on Impala for flight AEE2EG.
WARNING:root:No data on Impala for flight WZZ619.
WARNING:root:No data on Impala for flight WZZ867.
WARNING:root:No data on Impala for flight SAS4823.
WARNING:root:No data on Impala for flight WZZ433.
WARNING:root:No data on Impala for flight SAS4824.
WARNING:root:No data on Impala for flight SAS1816.
WARNING:root:No data on Impala for flight NAX1HD.
WARNING:root:No data on Impala for flight NAX2GY.
WARNING:root:No data on Impala for flight NAX3YO.
WARNING:root:No data on Impala for flight NAX6JS.
WARNING:root:No data on Impala for flight NAX7JP.
WARNING:root:No data on Impala for flight NAX21B.
WARNING:root:No data on Impala for flight NAX4VC.
WARNING:root:No data on Impala for flight NAX42N.
WARNING:root:No data on Impala for flight NAX5VD.
WARNING:root:No data on Impala for flight NAX13PT.
WARNING:root:No data on Impala for flight NAX14VN.
WARNING:root:No data on Impala for flight NAX3CX.
WARNING:root:No data on Impala for flight NAX3YL.
WARNING:root:No data on Impala for flight NAX1KB.
WARNING:root:No data on Impala for flight NAX2ZY.
WARNING:root:No data on Impala for flight NAX37N.
WARNING:root:No data on Impala for flight NAX47E.
WARNING:root:No data on Impala for flight NAX6LK.
WARNING:root:No data on Impala for flight NAX3NG.
WARNING:root:No data on Impala for flight NAX2WZ.
WARNING:root:No data on Impala for flight SAS74E.
WARNING:root:No data on Impala for flight SAS793.
WARNING:root:No data on Impala for flight SAS53P.
WARNING:root:No data on Impala for flight KLM39S.
WARNING:root:No data on Impala for flight KLM1258.
WARNING:root:No data on Impala for flight TRA16J.
WARNING:root:No data on Impala for flight KLM69M.
WARNING:root:No data on Impala for flight KLM78Q.
WARNING:root:No data on Impala for flight KLM33T.
WARNING:root:No data on Impala for flight KLM1596.
WARNING:root:No data on Impala for flight TRA46K.
WARNING:root:No data on Impala for flight TRA421U.
WARNING:root:No data on Impala for flight KLM1598.
WARNING:root:No data on Impala for flight TRA18U.
WARNING:root:No data on Impala for flight TRA9Y.
WARNING:root:No data on Impala for flight TRA47W.
WARNING:root:No data on Impala for flight TRA70X.
WARNING:root:No data on Impala for flight KLM591.
WARNING:root:No data on Impala for flight KLM103.
WARNING:root:No data on Impala for flight KLM1630.
WARNING:root:No data on Impala for flight TRA84P.
WARNING:root:No data on Impala for flight TRA93U.
WARNING:root:No data on Impala for flight KLM1253.
WARNING:root:No data on Impala for flight KLM48C.
WARNING:root:No data on Impala for flight KLM1592.
WARNING:root:No data on Impala for flight KLM81K.
WARNING:root:No data on Impala for flight TRA54U.
WARNING:root:No data on Impala for flight CND113.
WARNING:root:No data on Impala for flight CND114.
WARNING:root:No data on Impala for flight TRA71H.
WARNING:root:No data on Impala for flight TRA1626.
WARNING:root:No data on Impala for flight TRA77N.
WARNING:root:No data on Impala for flight KLM1567.
WARNING:root:No data on Impala for flight KLM66V.
WARNING:root:No data on Impala for flight KLM24H.
WARNING:root:No data on Impala for flight ENT7128.
WARNING:root:No data on Impala for flight ENT7129.
WARNING:root:No data on Impala for flight ENT778.
WARNING:root:No data on Impala for flight ENT437.
WARNING:root:No data on Impala for flight ENT7366.
WARNING:root:No data on Impala for flight ENT438.
WARNING:root:No data on Impala for flight LLX5431.
WARNING:root:No data on Impala for flight LLX5432.
WARNING:root:No data on Impala for flight LLX5433.
WARNING:root:No data on Impala for flight LLP342A.
WARNING:root:No data on Impala for flight LLP6135.
WARNING:root:No data on Impala for flight LOT437.
WARNING:root:No data on Impala for flight NJE520P.
WARNING:root:No data on Impala for flight LOT433.
WARNING:root:No data on Impala for flight NJE909R.
WARNING:root:No data on Impala for flight TAP551.
WARNING:root:No data on Impala for flight TAP557J.
WARNING:root:No data on Impala for flight TAP1305.
WARNING:root:No data on Impala for flight TAP1272.
WARNING:root:No data on Impala for flight TAP1235.
WARNING:root:No data on Impala for flight HFY312P.
WARNING:root:No data on Impala for flight TAP1312.
WARNING:root:No data on Impala for flight TAP1273.
WARNING:root:No data on Impala for flight TAP1274.
WARNING:root:No data on Impala for flight TAP573.
WARNING:root:No data on Impala for flight TAP553.
WARNING:root:No data on Impala for flight TAP1262.
WARNING:root:No data on Impala for flight TVS2799.
WARNING:root:No data on Impala for flight CSA5DE.
WARNING:root:No data on Impala for flight CSA5DF.
WARNING:root:No data on Impala for flight AIZ745.
WARNING:root:No data on Impala for flight AIZ746.
WARNING:root:No data on Impala for flight TVS2436.
WARNING:root:No data on Impala for flight TVS2437.
WARNING:root:No data on Impala for flight TVS2453.
WARNING:root:No data on Impala for flight TVS2452.
WARNING:root:No data on Impala for flight TVS6X.
WARNING:root:No data on Impala for flight ROT383R.
WARNING:root:No data on Impala for flight BMS2HX.
WARNING:root:No data on Impala for flight ROT381H.
WARNING:root:No data on Impala for flight BMS5516.
WARNING:root:No data on Impala for flight ROT382W.
WARNING:root:No data on Impala for flight ADR322.
WARNING:root:No data on Impala for flight ADR323.
WARNING:root:No data on Impala for flight ADR342.
WARNING:root:No data on Impala for flight CND516.
WARNING:root:No data on Impala for flight SAS4703.
WARNING:root:No data on Impala for flight SAS4704.
WARNING:root:No data on Impala for flight BLX425.
WARNING:root:No data on Impala for flight BLX735.
WARNING:root:No data on Impala for flight BLX553.
WARNING:root:No data on Impala for flight BLX426.
WARNING:root:No data on Impala for flight SAS2806.
WARNING:root:No data on Impala for flight SAS67W.
WARNING:root:No data on Impala for flight BCS7079.
WARNING:root:No data on Impala for flight HBJGP.
WARNING:root:No data on Impala for flight PGT38L.
WARNING:root:No data on Impala for flight PGT93J.
WARNING:root:No data on Impala for flight KKK2EY.
WARNING:root:No data on Impala for flight THY1MP.
WARNING:root:No data on Impala for flight THY9PG.
WARNING:root:No data on Impala for flight THY78C.
WARNING:root:No data on Impala for flight THY12.
WARNING:root:No data on Impala for flight THY6.
WARNING:root:No data on Impala for flight THY183.
WARNING:root:No data on Impala for flight THY6DC.
WARNING:root:No data on Impala for flight THY75Z.
WARNING:root:No data on Impala for flight THY82M.
WARNING:root:No data on Impala for flight THY4QM.
WARNING:root:No data on Impala for flight THY4QR.
WARNING:root:No data on Impala for flight THY36.
WARNING:root:No data on Impala for flight THY7WR.
WARNING:root:No data on Impala for flight THY9SC.
WARNING:root:No data on Impala for flight THY6DG.
WARNING:root:No data on Impala for flight THY2.
WARNING:root:No data on Impala for flight THY34.
WARNING:root:No data on Impala for flight THY8.
WARNING:root:No data on Impala for flight THY2AS.
WARNING:root:No data on Impala for flight THY2FM.
WARNING:root:No data on Impala for flight MNB351.
WARNING:root:No data on Impala for flight PGT75K.
WARNING:root:No data on Impala for flight PGT89P.
WARNING:root:No data on Impala for flight TWI782.
WARNING:root:No data on Impala for flight ASL16W.
WARNING:root:No data on Impala for flight ASL43Y.
WARNING:root:No data on Impala for flight ASL68Q.
WARNING:root:No data on Impala for flight ASL98F.
WARNING:root:No data on Impala for flight FCB326.
WARNING:root:No data on Impala for flight FCB327.
WARNING:root:No data on Impala for flight FCB682.
WARNING:root:No data on Impala for flight FCB658.
WARNING:root:No data on Impala for flight FCB379.
WARNING:root:No data on Impala for flight EIN40X.
WARNING:root:No data on Impala for flight TVS5GJ.
WARNING:root:No data on Impala for flight RYR31CR.
WARNING:root:No data on Impala for flight RYR2581.
WARNING:root:No data on Impala for flight RYR45JM.
WARNING:root:No data on Impala for flight RYR88CW.
WARNING:root:No data on Impala for flight RYR79PA.
WARNING:root:No data on Impala for flight RYR604W.
WARNING:root:No data on Impala for flight RYR30VA.
WARNING:root:No data on Impala for flight RYR47ZP.
WARNING:root:No data on Impala for flight RYR27XL.
WARNING:root:No data on Impala for flight RYR31KY.
WARNING:root:No data on Impala for flight RYR31HZ.
WARNING:root:No data on Impala for flight RYR76WB.
WARNING:root:No data on Impala for flight RYR5604.
WARNING:root:No data on Impala for flight RYR90GF.
WARNING:root:No data on Impala for flight RYR986A.
WARNING:root:No data on Impala for flight RYR843H.
WARNING:root:No data on Impala for flight RYR17XT.
WARNING:root:No data on Impala for flight RYR67CH.
WARNING:root:No data on Impala for flight RYR8414.
WARNING:root:No data on Impala for flight RYR16MJ.
WARNING:root:No data on Impala for flight RYR300P.
WARNING:root:No data on Impala for flight RYR30HG.
WARNING:root:No data on Impala for flight EIN416.
WARNING:root:No data on Impala for flight EIN451.
WARNING:root:No data on Impala for flight RYR7211.
WARNING:root:No data on Impala for flight RYR79ZR.
WARNING:root:No data on Impala for flight RYR87LL.
WARNING:root:No data on Impala for flight RYR71BQ.
WARNING:root:No data on Impala for flight RYR94FT.
WARNING:root:No data on Impala for flight RYR218H.
WARNING:root:No data on Impala for flight RYR143F.
WARNING:root:No data on Impala for flight RYR248Z.
WARNING:root:No data on Impala for flight RYR70ZG.
WARNING:root:No data on Impala for flight RYR69VB.
WARNING:root:No data on Impala for flight RYR98RM.
WARNING:root:No data on Impala for flight RYR3Z.
WARNING:root:No data on Impala for flight RYS3405.
WARNING:root:No data on Impala for flight RYR52TK.
WARNING:root:No data on Impala for flight RYR829J.
WARNING:root:No data on Impala for flight RYR1911.
WARNING:root:No data on Impala for flight RYR2765.
WARNING:root:No data on Impala for flight RYR60AU.
WARNING:root:No data on Impala for flight RYR175R.
WARNING:root:No data on Impala for flight RYR3746.
WARNING:root:No data on Impala for flight RYR263C.
WARNING:root:No data on Impala for flight RYR8809.
WARNING:root:No data on Impala for flight RYR73FZ.
WARNING:root:No data on Impala for flight RYR438V.
WARNING:root:No data on Impala for flight RYR83HB.
WARNING:root:No data on Impala for flight RYR87WH.
WARNING:root:No data on Impala for flight LDM663.
WARNING:root:No data on Impala for flight LDM669.
WARNING:root:No data on Impala for flight LDM20A.
WARNING:root:No data on Impala for flight LDM303.
WARNING:root:No data on Impala for flight IBK2UM.
WARNING:root:No data on Impala for flight IBK5GR.
WARNING:root:No data on Impala for flight IBK6693.
WARNING:root:No data on Impala for flight IBK5602.
WARNING:root:No data on Impala for flight RYR18GT.
WARNING:root:No data on Impala for flight IBK1RG.
WARNING:root:No data on Impala for flight IBK6686.
WARNING:root:No data on Impala for flight IBK6687.
WARNING:root:No data on Impala for flight LDM665.
WARNING:root:No data on Impala for flight RYR4W.
WARNING:root:No data on Impala for flight IBK1023.
WARNING:root:No data on Impala for flight IBK9RU.
WARNING:root:No data on Impala for flight IBK5621.
WARNING:root:No data on Impala for flight IBK1021.
WARNING:root:No data on Impala for flight IBK6LE.
WARNING:root:No data on Impala for flight RYR20WP.
WARNING:root:No data on Impala for flight RYR51DP.
WARNING:root:No data on Impala for flight RYR22KL.
WARNING:root:No data on Impala for flight RYR675R.
WARNING:root:No data on Impala for flight RYR79VD.
WARNING:root:No data on Impala for flight RYR89JH.
WARNING:root:No data on Impala for flight IBK5106.
WARNING:root:No data on Impala for flight RYR29QL.
WARNING:root:No data on Impala for flight RYR952P.
WARNING:root:No data on Impala for flight RYR233Y.
WARNING:root:No data on Impala for flight RYR1069.
WARNING:root:No data on Impala for flight RYR2744.
WARNING:root:No data on Impala for flight RYR739D.
WARNING:root:No data on Impala for flight IBK5402.
WARNING:root:No data on Impala for flight IBK4CT.
WARNING:root:No data on Impala for flight IBK538.
WARNING:root:No data on Impala for flight RYR1M.
WARNING:root:No data on Impala for flight RYR39PH.
WARNING:root:No data on Impala for flight RYR16QG.
WARNING:root:No data on Impala for flight RYR588J.
WARNING:root:No data on Impala for flight RYR59DW.
WARNING:root:No data on Impala for flight RYR59JT.
WARNING:root:No data on Impala for flight RYR1888.
WARNING:root:No data on Impala for flight RYR5184.
WARNING:root:No data on Impala for flight RYR97WG.
WARNING:root:No data on Impala for flight RYR81HY.
WARNING:root:No data on Impala for flight RYR32BR.
WARNING:root:No data on Impala for flight RYR17UU.
WARNING:root:No data on Impala for flight IBK2MC.
WARNING:root:No data on Impala for flight IBK3NU.
WARNING:root:No data on Impala for flight RYR9102.
WARNING:root:No data on Impala for flight LDM32.
WARNING:root:No data on Impala for flight LDM33.
WARNING:root:No data on Impala for flight RYR47DU.
WARNING:root:No data on Impala for flight RYR55NF.
WARNING:root:No data on Impala for flight RYR25EF.
WARNING:root:No data on Impala for flight RYR28BB.
WARNING:root:No data on Impala for flight RYR90XD.
WARNING:root:No data on Impala for flight RYR40RY.
WARNING:root:No data on Impala for flight EIN42K.
WARNING:root:No data on Impala for flight AZA108.
WARNING:root:No data on Impala for flight IBK3640.
WARNING:root:No data on Impala for flight IBK3641.
WARNING:root:No data on Impala for flight IBK56V.
WARNING:root:No data on Impala for flight IBK365L.
WARNING:root:No data on Impala for flight RYR63VF.
WARNING:root:No data on Impala for flight RYR103U.
WARNING:root:No data on Impala for flight RYR4252.
WARNING:root:No data on Impala for flight IBK9549.
WARNING:root:No data on Impala for flight IBK64N.
WARNING:root:No data on Impala for flight RYR411T.
WARNING:root:No data on Impala for flight RYR715.
WARNING:root:No data on Impala for flight RYR34UU.
WARNING:root:No data on Impala for flight RYR65XX.
WARNING:root:No data on Impala for flight RYR27ZZ.
WARNING:root:No data on Impala for flight RYR380N.
WARNING:root:No data on Impala for flight RYR52BD.
WARNING:root:No data on Impala for flight RYR93VT.
WARNING:root:No data on Impala for flight RYR6K.
WARNING:root:No data on Impala for flight RYR70WM.
WARNING:root:No data on Impala for flight RYR832X.
WARNING:root:No data on Impala for flight AZA324.
WARNING:root:No data on Impala for flight EIN40W.
WARNING:root:No data on Impala for flight AZA97U.
WARNING:root:No data on Impala for flight RYR639V.
WARNING:root:No data on Impala for flight RYR78SK.
WARNING:root:No data on Impala for flight RYR8W.
WARNING:root:No data on Impala for flight RYR91WG.
WARNING:root:No data on Impala for flight LDM315.
WARNING:root:No data on Impala for flight RYR79SV.
WARNING:root:No data on Impala for flight RYR705U.
WARNING:root:No data on Impala for flight RYR15DG.
WARNING:root:No data on Impala for flight RYR58LW.
WARNING:root:No data on Impala for flight IBK3668.
WARNING:root:No data on Impala for flight RYR85NN.
WARNING:root:No data on Impala for flight IBK36FS.
WARNING:root:No data on Impala for flight RYR87BG.
WARNING:root:No data on Impala for flight RYR96SL.
WARNING:root:No data on Impala for flight RYR137W.
WARNING:root:No data on Impala for flight RYR159.
WARNING:root:No data on Impala for flight RYR40NF.
WARNING:root:No data on Impala for flight RYR51FH.
WARNING:root:No data on Impala for flight RYR559F.
WARNING:root:No data on Impala for flight LDM89.
WARNING:root:No data on Impala for flight AZA20Y.
WARNING:root:No data on Impala for flight AZA156.
WARNING:root:No data on Impala for flight RYR9R.
WARNING:root:No data on Impala for flight RYR63SJ.
WARNING:root:No data on Impala for flight RYR347U.
WARNING:root:No data on Impala for flight RYR38GV.
WARNING:root:No data on Impala for flight RYR4561.
WARNING:root:No data on Impala for flight RYR85VQ.
WARNING:root:No data on Impala for flight RYR51HH.
WARNING:root:No data on Impala for flight EIN428.
WARNING:root:No data on Impala for flight IBK9463.
WARNING:root:No data on Impala for flight IBK6622.
WARNING:root:No data on Impala for flight IBK6651.
WARNING:root:No data on Impala for flight IBK6505.
WARNING:root:No data on Impala for flight IBK6RE.
WARNING:root:No data on Impala for flight RYR3493.
WARNING:root:No data on Impala for flight RYR17CD.
WARNING:root:No data on Impala for flight RYR73FM.
WARNING:root:No data on Impala for flight RYR14RG.
WARNING:root:No data on Impala for flight RYR209H.
WARNING:root:No data on Impala for flight RYR21LP.
WARNING:root:No data on Impala for flight RYR58JR.
WARNING:root:No data on Impala for flight RYR632M.
WARNING:root:No data on Impala for flight RYR72AZ.
WARNING:root:No data on Impala for flight RYR87LT.
WARNING:root:No data on Impala for flight RYR26WE.
WARNING:root:No data on Impala for flight RYR42JK.
WARNING:root:No data on Impala for flight RYR67SZ.
WARNING:root:No data on Impala for flight RYR589C.
WARNING:root:No data on Impala for flight RYR758E.
WARNING:root:No data on Impala for flight AZA420.
WARNING:root:No data on Impala for flight RYR33SJ.
WARNING:root:No data on Impala for flight LDM316.
WARNING:root:No data on Impala for flight AZA403.
WARNING:root:No data on Impala for flight RYR39XC.
WARNING:root:No data on Impala for flight RYR74SK.
WARNING:root:No data on Impala for flight RYR730M.
WARNING:root:No data on Impala for flight LDM141.
WARNING:root:No data on Impala for flight AZA31Z.
WARNING:root:No data on Impala for flight RYR76HN.
WARNING:root:No data on Impala for flight RYR95JQ.
WARNING:root:No data on Impala for flight RYR20JY.
WARNING:root:No data on Impala for flight RYR3475.
WARNING:root:No data on Impala for flight RYR2956.
WARNING:root:No data on Impala for flight RYR63BY.
WARNING:root:No data on Impala for flight RYR79PW.
WARNING:root:No data on Impala for flight RYR88EX.
WARNING:root:No data on Impala for flight RYR789Z.
WARNING:root:No data on Impala for flight RYR98TM.
WARNING:root:No data on Impala for flight RYR9382.
WARNING:root:No data on Impala for flight RYR95WD.
WARNING:root:No data on Impala for flight RYR39RH.
WARNING:root:No data on Impala for flight RYR98EN.
WARNING:root:No data on Impala for flight RYR186K.
WARNING:root:No data on Impala for flight RYR18MQ.
WARNING:root:No data on Impala for flight LDM522.
WARNING:root:No data on Impala for flight LDM523.
WARNING:root:No data on Impala for flight LDM524.
WARNING:root:No data on Impala for flight LDM525.
WARNING:root:No data on Impala for flight RYR6121.
WARNING:root:No data on Impala for flight RYR61WL.
WARNING:root:No data on Impala for flight RYR54EK.
WARNING:root:No data on Impala for flight RYR95CT.
WARNING:root:No data on Impala for flight RYR2497.
WARNING:root:No data on Impala for flight RYR42CT.
WARNING:root:No data on Impala for flight RYR50LY.
WARNING:root:No data on Impala for flight RYR75HU.
WARNING:root:No data on Impala for flight RYR34FY.
WARNING:root:No data on Impala for flight RYR129Y.
WARNING:root:No data on Impala for flight RYR31VL.
WARNING:root:No data on Impala for flight RYR3748.
WARNING:root:No data on Impala for flight RYR71CL.
WARNING:root:No data on Impala for flight RYR99UD.
WARNING:root:No data on Impala for flight RYR720C.
WARNING:root:No data on Impala for flight RYR74WK.
WARNING:root:No data on Impala for flight RYR21UX.
WARNING:root:No data on Impala for flight RYR12PU.
WARNING:root:No data on Impala for flight IBK5FL.
WARNING:root:No data on Impala for flight IBK4MD.
WARNING:root:No data on Impala for flight IBK6UK.
WARNING:root:No data on Impala for flight IBK7VR.
WARNING:root:No data on Impala for flight IBK9461.
WARNING:root:No data on Impala for flight IBK9460.
WARNING:root:No data on Impala for flight RYR98XZ.
WARNING:root:No data on Impala for flight RYR1AG.
WARNING:root:No data on Impala for flight RYR14EB.
WARNING:root:No data on Impala for flight RYR83DL.
WARNING:root:No data on Impala for flight RYR94JF.
WARNING:root:No data on Impala for flight ACP2623.
WARNING:root:No data on Impala for flight BEL64F.
WARNING:root:No data on Impala for flight IBK514.
WARNING:root:No data on Impala for flight LGL6556.
WARNING:root:No data on Impala for flight LGL8255.
WARNING:root:No data on Impala for flight LGL65R.
WARNING:root:No data on Impala for flight LGL8256.
WARNING:root:No data on Impala for flight LGL62PM.
WARNING:root:No data on Impala for flight LGL937.
WARNING:root:No data on Impala for flight LGL833.
WARNING:root:No data on Impala for flight LXA21V.
WARNING:root:No data on Impala for flight AMC329.
WARNING:root:No data on Impala for flight AMC394.
WARNING:root:No data on Impala for flight KER739.
WARNING:root:No data on Impala for flight VJT492.
WARNING:root:No data on Impala for flight VJT405.
WARNING:root:No data on Impala for flight VJT965.
WARNING:root:No data on Impala for flight VJT929.
WARNING:root:No data on Impala for flight VJT437.
WARNING:root:No data on Impala for flight TEU3.
WARNING:root:No data on Impala for flight AMC101.
WARNING:root:No data on Impala for flight AMC421.
WARNING:root:No data on Impala for flight T7STK.
WARNING:root:No data on Impala for flight T7STK.
WARNING:root:No data on Impala for flight CTN29F.
WARNING:root:No data on Impala for flight CTN476.
WARNING:root:No data on Impala for flight CTN25F.
WARNING:root:No data on Impala for flight CTN475.
WARNING:root:No data on Impala for flight CTN52R.
WARNING:root:No data on Impala for flight CTN71F.
WARNING:root:No data on Impala for flight PRI545.
WARNING:root:No data on Impala for flight PRW368.
WARNING:root:No data on Impala for flight EZY892U.
WARNING:root:No data on Impala for flight TCX1325.
WARNING:root:No data on Impala for flight TCX7RE.
WARNING:root:No data on Impala for flight TCX1823.
WARNING:root:No data on Impala for flight PRW778.
WARNING:root:No data on Impala for flight CFG2CY.
WARNING:root:No data on Impala for flight CFG2FL.
WARNING:root:No data on Impala for flight TAR734.
WARNING:root:No data on Impala for flight TAR735.
WARNING:root:No data on Impala for flight TAR440.
WARNING:root:No data on Impala for flight TAR634.
WARNING:root:No data on Impala for flight TCX1512.
WARNING:root:No data on Impala for flight TCX69RH.
WARNING:root:No data on Impala for flight TCX1077.
WARNING:root:No data on Impala for flight TCX16VC.
WARNING:root:No data on Impala for flight TCX56RM.
WARNING:root:No data on Impala for flight CFG2XH.
WARNING:root:No data on Impala for flight JAF3383.
WARNING:root:No data on Impala for flight JAF3384.
WARNING:root:No data on Impala for flight UPEM007.
WARNING:root:No data on Impala for flight SVA126.
WARNING:root:No data on Impala for flight OMA132.
WARNING:root:No data on Impala for flight SVA115.
WARNING:root:No data on Impala for flight SVA144.
WARNING:root:No data on Impala for flight SVA117.
WARNING:root:No data on Impala for flight SVA7021.
WARNING:root:No data on Impala for flight SVA123.
WARNING:root:No data on Impala for flight SVA124.
WARNING:root:No data on Impala for flight IAW239.
WARNING:root:No data on Impala for flight KAL915.
WARNING:root:No data on Impala for flight IRM106.
WARNING:root:No data on Impala for flight IRM107.
WARNING:root:No data on Impala for flight ELY226.
WARNING:root:No data on Impala for flight ELY325.
WARNING:root:No data on Impala for flight ELY320.
WARNING:root:No data on Impala for flight ELY319.
WARNING:root:No data on Impala for flight ELY323.
WARNING:root:No data on Impala for flight ELY328.
WARNING:root:No data on Impala for flight ELY324.
WARNING:root:No data on Impala for flight ELY026.
WARNING:root:No data on Impala for flight RJA111.
WARNING:root:No data on Impala for flight RJA126.
WARNING:root:No data on Impala for flight RJA268.
WARNING:root:No data on Impala for flight RJA262.
WARNING:root:No data on Impala for flight RJA264.
WARNING:root:No data on Impala for flight MEA211.
WARNING:root:No data on Impala for flight MEA212.
WARNING:root:No data on Impala for flight MEA210.
WARNING:root:No data on Impala for flight SIA335.
WARNING:root:No data on Impala for flight AIC143.
WARNING:root:No data on Impala for flight JAI123.
WARNING:root:No data on Impala for flight THA931.
WARNING:root:No data on Impala for flight HVN18.
WARNING:root:No data on Impala for flight HVN10.
WARNING:root:No data on Impala for flight GFA018.
WARNING:root:No data on Impala for flight UAE214.
WARNING:root:No data on Impala for flight ETD47N.
WARNING:root:No data on Impala for flight ETD97G.
WARNING:root:No data on Impala for flight UAE72.
WARNING:root:No data on Impala for flight ETD11K.
WARNING:root:No data on Impala for flight UAE74.
WARNING:root:No data on Impala for flight UAE93P.
WARNING:root:No data on Impala for flight EVA088.
WARNING:root:No data on Impala for flight N1624K.
WARNING:root:No data on Impala for flight UAL90.
WARNING:root:No data on Impala for flight CMBDQ1.
WARNING:root:No data on Impala for flight N329CH.
WARNING:root:No data on Impala for flight N375WB.
WARNING:root:No data on Impala for flight SJE500.
WARNING:root:No data on Impala for flight CKS9557.
WARNING:root:No data on Impala for flight FDX5238.
WARNING:root:No data on Impala for flight N79MA.
WARNING:root:No data on Impala for flight N815WH.
WARNING:root:No data on Impala for flight N9997X.
WARNING:root:No data on Impala for flight TSC300.
WARNING:root:No data on Impala for flight LAN705.

with plt.style.context('traffic'):
    fig, ax = plt.subplots(subplot_kw=dict(projection=EuroPP()))
ax.add_feature(countries())
ax.gridlines()
ax.set_extent((-7, 15, 40, 55))
# get only the positions detected by your sensors
sv = opensky.api_states(True)
sv.plot(ax, s=20)
for sensor in opensky.api_sensors:
    c = opensky.api_range(sensor)
c.plot(ax, linewidth=2, edgecolor='grey', linestyle='dashed')
c.point.plot(ax, marker='x', text_kw=dict(s=c.point.name))

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1769423602.py in <module>
      5 ax.set_extent((-7, 15, 40, 55))
      6 # get only the positions detected by your sensors
----> 7 sv = opensky.api_states(True)
      8 sv.plot(ax, s=20)
      9 for sensor in opensky.api_sensors:

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/traffic/data/adsb/opensky.py in api_states(self, own, bounds)
    232         )
    233         c.raise_for_status()
--> 234         r = pd.DataFrame.from_records(
    235             c.json()["states"], columns=self._json_columns
    236         )

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/frame.py in from_records(cls, data, index, exclude, columns, coerce_float, nrows)
   2071             arr_columns = columns
   2072         else:
-> 2073             arrays, arr_columns = to_arrays(data, columns)
   2074             if coerce_float:
   2075                 for i, arr in enumerate(arrays):

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/pandas/core/internals/construction.py in to_arrays(data, columns, dtype)
    756         return arrays, columns
    757 
--> 758     if not len(data):
    759         if isinstance(data, np.ndarray):
    760             if data.dtype.names is not None:

TypeError: object of type 'NoneType' has no len()

opensky.api_arrival('EGPF', '2021-10-30 11:11', '2021-11-02 13:42')

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport
243	2021-10-30 10:40:40+00:00	2021-10-30 11:17:37+00:00	400dc2	GMA01	None	EGPF
242	2021-10-30 04:23:09+00:00	2021-10-30 11:32:18+00:00	8963df	UAE27	OMDB	EGPF
241	2021-10-30 10:54:16+00:00	2021-10-30 12:00:59+00:00	40781b	CBM66	EGFF	EGPF
240	2021-10-30 11:12:37+00:00	2021-10-30 12:04:12+00:00	40643c	EZY675L	EGSS	EGPF
239	2021-10-30 10:05:04+00:00	2021-10-30 12:21:10+00:00	4078a4	UKP154	EGCN	EGPF
...	...	...	...	...	...	...
4	2021-11-02 12:54:57+00:00	2021-11-02 13:06:15+00:00	05e057	MRT001	EGPK	EGPF
3	2021-11-02 12:50:49+00:00	2021-11-02 13:13:29+00:00	45f425	DAF9974	EGPE	EGPF
2	2021-11-02 12:58:07+00:00	2021-11-02 13:27:51+00:00	406df5	GSGTS	None	EGPF
1	2021-11-02 12:28:43+00:00	2021-11-02 13:30:55+00:00	406b91	EZY861P	EGGD	EGPF
0	2021-11-02 12:20:50+00:00	2021-11-02 13:32:10+00:00	4077c8	HLE02	EGPE	EGPF

244 rows × 6 columns

from traffic.data import airports, navaids, eurofirs
airports["EGPF"] # accessible through "ZRH" as well
navaids.extent("Scotland")["GLA"] # ZURICH EAST VOR-DME
# eurofirs["EGPF"] # SWITZERLAND FIR

# Mercator projection is the default one with Altair
quickstart["AFR27GH"].geoencode().project(type="mercator")

before_COP = (
    pre_data.clean_invalid()
    .assign_id()  # helps counting the number of flight rather than aircraft
    .filter()  # filter abnormal values
    .resample("10s")  # we don't need so many points for a heatmap
    .eval(desc="", max_workers=4)  # multiprocessed (watch your RAM usage!)
)

# after_covid19 = (
#     post_data.clean_invalid()
#     .assign_id()
#     .filter()
#     .resample("10s")
#     .eval(desc="", max_workers=4)
# )

# Saving data (optional)

# before_COP.to_pickle("before_covid19.pkl")
# after_covid19.to_pickle("after_covid19.pkl")

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/325631725.py in <module>
      1 before_COP = (
----> 2     pre_data.assign_id()  # helps counting the number of flight rather than aircraft
      3     .filter()  # filter abnormal values
      4     .resample("10s")  # we don't need so many points for a heatmap
      5     .eval(desc="", max_workers=4)  # multiprocessed (watch your RAM usage!)

AttributeError: 'NoneType' object has no attribute 'assign_id'

with plt.style.context("traffic"):

    fig = plt.figure(figsize=(15, 10), frameon=False)
    ax = fig.subplots(1, 2, subplot_kw=dict(projection=EuroPP()))

    for ax_ in ax:
        ax_.add_feature(countries(scale="50m", linewidth=1.5))
        ax_.background_patch.set_facecolor("#eeeeee")

    vmax = None  # this trick will keep the same colorbar scale for both maps

    for i, data in enumerate([pre_data]):
        cax = (
            data.query("altitude > 10000")
            .agg_latlon(
                # 10 points per integer lat/lon
                resolution=dict(latitude=10, longitude=10),
                # count the number of flights
                flight_id="nunique"
            ).query(f"flight_id > 10")  # do not display outlier flights
            .to_xarray()
            .flight_id.plot.pcolormesh(
                ax=ax[i],
                cmap="YlOrBr",
                transform=PlateCarree(),
                vmax=vmax,
                add_colorbar=False,
            )
        )

        cbaxes = inset_axes(ax[i], "4%", "60%", loc=3)
        cb = fig.colorbar(cax, cax=cbaxes)

        # keep this value to scale the colorbar for the second day
        vmax = cb.vmax

        text = AnchoredText(
            f"{data.start_time:%B %d, %Y}",
            loc=1,
            prop={"size": 24, "fontname": "Ubuntu"},
            frameon=True,
        )
        text.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
        ax[i].add_artist(text)

    fig.set_tight_layout(True)

/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1772923626.py:8: DeprecationWarning: The background_patch property is deprecated. Use GeoAxes.patch instead.
  ax_.background_patch.set_facecolor("#eeeeee")

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1772923626.py in <module>
     12     for i, data in enumerate([pre_data]):
     13         cax = (
---> 14             data.query("altitude > 10000")
     15             .agg_latlon(
     16                 # 10 points per integer lat/lon

AttributeError: 'NoneType' object has no attribute 'query'

ERROR:fiona._env:PROJ: proj_identify: /Users/aliciaadams/opt/anaconda3/envs/Flights/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.

flight = opensky.history(
    "2017-02-05",
    # stop is implicit, i.e. stop="2017-02-06"
    callsign="EZY158T",
    return_flight=True
)

from traffic.data import eurofirs
from traffic.data.samples import switzerland
df = opensky.extended(
switzerland.start_time,
switzerland.end_time,
bounds=eurofirs['LSAS']
)
enriched_ch = (
switzerland
.filter()
.query_ehs(df)
.resample('1s')
.eval(desc='', max_workers=4)
)

WARNING:root:No data on Impala for flight MSR986.
WARNING:root:No data on Impala for flight SAA260.
WARNING:root:No data on Impala for flight SAA261.
WARNING:root:No data on Impala for flight MSR799.
WARNING:root:No data on Impala for flight MSR801.
WARNING:root:No data on Impala for flight MSR777.
WARNING:root:No data on Impala for flight MSR800.
WARNING:root:No data on Impala for flight MSR779.
WARNING:root:No data on Impala for flight RAM816C.
WARNING:root:No data on Impala for flight RAM811D.
WARNING:root:No data on Impala for flight TAR724.
WARNING:root:No data on Impala for flight MAC223.
WARNING:root:No data on Impala for flight MAC612.
WARNING:root:No data on Impala for flight TAR6647.
WARNING:root:No data on Impala for flight TAR836.
WARNING:root:No data on Impala for flight TAR6541.
WARNING:root:No data on Impala for flight TAR6540.
WARNING:root:No data on Impala for flight TAR788.
WARNING:root:No data on Impala for flight TAR789.
WARNING:root:No data on Impala for flight TAR744.
WARNING:root:No data on Impala for flight TAR745.
WARNING:root:No data on Impala for flight TAR526.
WARNING:root:No data on Impala for flight LBT5360.
WARNING:root:No data on Impala for flight LBT586.
WARNING:root:No data on Impala for flight TAR527.
WARNING:root:No data on Impala for flight ETH705.
WARNING:root:No data on Impala for flight RAM688.
WARNING:root:No data on Impala for flight ETH710.
WARNING:root:No data on Impala for flight TAR668.
WARNING:root:No data on Impala for flight KQA117.
WARNING:root:No data on Impala for flight MAU46.
WARNING:root:No data on Impala for flight MDG053.
WARNING:root:No data on Impala for flight MAU34.
WARNING:root:No data on Impala for flight QTR778.
WARNING:root:No data on Impala for flight QTR7XB.
WARNING:root:No data on Impala for flight DAH2062.
WARNING:root:No data on Impala for flight DAH2063.
WARNING:root:No data on Impala for flight DAH2070.
WARNING:root:No data on Impala for flight NMB286A.
WARNING:root:No data on Impala for flight DAH2071.
WARNING:root:No data on Impala for flight DAH1175.
WARNING:root:No data on Impala for flight AZA88Z.
WARNING:root:No data on Impala for flight AZA74F.
WARNING:root:No data on Impala for flight RA67243.
WARNING:root:No data on Impala for flight AZA165.
WARNING:root:No data on Impala for flight DLH3EM.
WARNING:root:No data on Impala for flight DLH4KY.
WARNING:root:No data on Impala for flight DLH9XT.
WARNING:root:No data on Impala for flight VLG86TM.
WARNING:root:No data on Impala for flight DLH7TJ.
WARNING:root:No data on Impala for flight DLH8JW.
WARNING:root:No data on Impala for flight IBS3674.
WARNING:root:No data on Impala for flight PVG7344.
WARNING:root:No data on Impala for flight PVG7345.
WARNING:root:No data on Impala for flight AEA1516.
WARNING:root:No data on Impala for flight IBE31CW.
WARNING:root:No data on Impala for flight IBE3147.
WARNING:root:No data on Impala for flight IBE3284.
WARNING:root:No data on Impala for flight IBE31BV.
WARNING:root:No data on Impala for flight VLG62RE.
WARNING:root:No data on Impala for flight VLG62VE.
WARNING:root:No data on Impala for flight IBE32VL.
WARNING:root:No data on Impala for flight IBE3122.
WARNING:root:No data on Impala for flight VLG8992.
WARNING:root:No data on Impala for flight IBE3195.
WARNING:root:No data on Impala for flight IBE31AV.
WARNING:root:No data on Impala for flight VLG12HE.
WARNING:root:No data on Impala for flight IBE3149.
WARNING:root:No data on Impala for flight VLG24ZG.
WARNING:root:No data on Impala for flight VLG62CF.
WARNING:root:No data on Impala for flight IBE31TT.
WARNING:root:No data on Impala for flight VLG2470.
WARNING:root:No data on Impala for flight VLG8546.
WARNING:root:No data on Impala for flight VLG6292.
WARNING:root:No data on Impala for flight IBE32AY.
WARNING:root:No data on Impala for flight IBE3279.
WARNING:root:No data on Impala for flight VLG960.
WARNING:root:No data on Impala for flight VLG18TB.
WARNING:root:No data on Impala for flight VLG64MN.
WARNING:root:No data on Impala for flight VLG18KA.
WARNING:root:No data on Impala for flight VLG1893.
WARNING:root:No data on Impala for flight IBE3128.
WARNING:root:No data on Impala for flight VLG56RH.
WARNING:root:No data on Impala for flight IBE3129.
WARNING:root:No data on Impala for flight VLG15XC.
WARNING:root:No data on Impala for flight VLG6206.
WARNING:root:No data on Impala for flight VLG18HA.
WARNING:root:No data on Impala for flight VLG67MT.
WARNING:root:No data on Impala for flight VLG1502.
WARNING:root:No data on Impala for flight VLG15MB.
WARNING:root:No data on Impala for flight VLG6815.
WARNING:root:No data on Impala for flight AEA1518.
WARNING:root:No data on Impala for flight CFG4LW.
WARNING:root:No data on Impala for flight VLG20N.
WARNING:root:No data on Impala for flight CFG3PW.
WARNING:root:No data on Impala for flight CFG4AK.
WARNING:root:No data on Impala for flight VOE15AZ.
WARNING:root:No data on Impala for flight CFG8EH.
WARNING:root:No data on Impala for flight AEA1502.
WARNING:root:No data on Impala for flight AFR1294.
WARNING:root:No data on Impala for flight CFG4CL.
WARNING:root:No data on Impala for flight AFR29FV.
WARNING:root:No data on Impala for flight AFR13LC.
WARNING:root:No data on Impala for flight AFR1085.
WARNING:root:No data on Impala for flight AFR73ZC.
WARNING:root:No data on Impala for flight AFR92ZD.
WARNING:root:No data on Impala for flight AFR52JV.
WARNING:root:No data on Impala for flight AFR120Z.
WARNING:root:No data on Impala for flight AFR31LZ.
WARNING:root:No data on Impala for flight AFR1321.
WARNING:root:No data on Impala for flight AFR218.
WARNING:root:No data on Impala for flight AFR244.
WARNING:root:No data on Impala for flight AFR16PQ.
WARNING:root:No data on Impala for flight AFR129P.
WARNING:root:No data on Impala for flight AFR59VK.
WARNING:root:No data on Impala for flight AFR49LZ.
WARNING:root:No data on Impala for flight AFR53NA.
WARNING:root:No data on Impala for flight AFR81CU.
WARNING:root:No data on Impala for flight AFR51ZG.
WARNING:root:No data on Impala for flight AFR75LV.
WARNING:root:No data on Impala for flight AFR56YH.
WARNING:root:No data on Impala for flight AFR103W.
WARNING:root:No data on Impala for flight AFR79JA.
WARNING:root:No data on Impala for flight HOP25XY.
WARNING:root:No data on Impala for flight AFR65DC.
WARNING:root:No data on Impala for flight AFR172W.
WARNING:root:No data on Impala for flight AFR52WL.
WARNING:root:No data on Impala for flight AFR188Q.
WARNING:root:No data on Impala for flight AFR85EZ.
WARNING:root:No data on Impala for flight AFR935.
WARNING:root:No data on Impala for flight AFR67NL.
WARNING:root:No data on Impala for flight AFR565.
WARNING:root:No data on Impala for flight AFR662.
WARNING:root:No data on Impala for flight AFR645.
WARNING:root:No data on Impala for flight AFR11ZQ.
WARNING:root:No data on Impala for flight AFR12MV.
WARNING:root:No data on Impala for flight AFR81MZ.
WARNING:root:No data on Impala for flight AFR49YR.
WARNING:root:No data on Impala for flight AFR182U.
WARNING:root:No data on Impala for flight AFR36RB.
WARNING:root:No data on Impala for flight AFR53FL.
WARNING:root:No data on Impala for flight AFR48YH.
WARNING:root:No data on Impala for flight AFR77MM.
WARNING:root:No data on Impala for flight AFR26EH.
WARNING:root:No data on Impala for flight AFR94FA.
WARNING:root:No data on Impala for flight AFR93FU.
WARNING:root:No data on Impala for flight AFR22CR.
WARNING:root:No data on Impala for flight AFR74SW.
WARNING:root:No data on Impala for flight AFR79BT.
WARNING:root:No data on Impala for flight AFR23GH.
WARNING:root:No data on Impala for flight AFR139J.
WARNING:root:No data on Impala for flight AFR34JV.
WARNING:root:No data on Impala for flight AFR1767.
WARNING:root:No data on Impala for flight AFR64GD.
WARNING:root:No data on Impala for flight AFR156N.
WARNING:root:No data on Impala for flight AFR1267.
WARNING:root:No data on Impala for flight AFR102M.
WARNING:root:No data on Impala for flight AFR149T.
WARNING:root:No data on Impala for flight AFR71UL.
WARNING:root:No data on Impala for flight AFR91AX.
WARNING:root:No data on Impala for flight AFR33HZ.
WARNING:root:No data on Impala for flight TVF58WV.
WARNING:root:No data on Impala for flight TVF3589.
WARNING:root:No data on Impala for flight AFR6746.
WARNING:root:No data on Impala for flight TVF63MW.
WARNING:root:No data on Impala for flight TVF60GQ.
WARNING:root:No data on Impala for flight TVF23PW.
WARNING:root:No data on Impala for flight TVF99TR.
WARNING:root:No data on Impala for flight TVF90LP.
WARNING:root:No data on Impala for flight TVF88AK.
WARNING:root:No data on Impala for flight TVF91BR.
WARNING:root:No data on Impala for flight TVF17ZE.
WARNING:root:No data on Impala for flight TVF98DJ.
WARNING:root:No data on Impala for flight TVF91ZJ.
WARNING:root:No data on Impala for flight TVF51ZP.
WARNING:root:No data on Impala for flight TVF53KM.
WARNING:root:No data on Impala for flight TVF62SY.
WARNING:root:No data on Impala for flight TVF91RK.
WARNING:root:No data on Impala for flight TVF78DA.
WARNING:root:No data on Impala for flight TVF23GR.
WARNING:root:No data on Impala for flight TVF83AF.
WARNING:root:No data on Impala for flight TVF10VL.
WARNING:root:No data on Impala for flight FPO09P.
WARNING:root:No data on Impala for flight FPO10Q.
WARNING:root:No data on Impala for flight XLF346.
WARNING:root:No data on Impala for flight AAF627.
WARNING:root:No data on Impala for flight CCM752B.
WARNING:root:No data on Impala for flight FHBTV.
WARNING:root:No data on Impala for flight AFR16TR.
WARNING:root:No data on Impala for flight AFR57DD.
WARNING:root:No data on Impala for flight AFR132E.
WARNING:root:No data on Impala for flight CCM753X.
WARNING:root:No data on Impala for flight AFR1620.
WARNING:root:No data on Impala for flight AFR452.
WARNING:root:No data on Impala for flight AFR1621.
WARNING:root:No data on Impala for flight AFR1228.
WARNING:root:No data on Impala for flight AFR1752.
WARNING:root:No data on Impala for flight AFR65UU.
WARNING:root:No data on Impala for flight FBU703.
WARNING:root:No data on Impala for flight AFR55KX.
WARNING:root:No data on Impala for flight CRL905.
WARNING:root:No data on Impala for flight AFR814.
WARNING:root:No data on Impala for flight TVF07BA.
WARNING:root:No data on Impala for flight TVF22HV.
WARNING:root:No data on Impala for flight TVF788Z.
WARNING:root:No data on Impala for flight IXR501G.
WARNING:root:No data on Impala for flight TVF74PX.
WARNING:root:No data on Impala for flight CCM771F.
WARNING:root:No data on Impala for flight CCM531D.
WARNING:root:No data on Impala for flight CCM776Y.
WARNING:root:No data on Impala for flight CCM775Q.
WARNING:root:No data on Impala for flight CCM777H.
WARNING:root:No data on Impala for flight CCM793N.
WARNING:root:No data on Impala for flight CCM778K.
WARNING:root:No data on Impala for flight CCM792N.
WARNING:root:No data on Impala for flight REU977.
WARNING:root:No data on Impala for flight REU971.
WARNING:root:No data on Impala for flight SDR2433.
WARNING:root:No data on Impala for flight SDR6436.
WARNING:root:No data on Impala for flight LLX5932.
WARNING:root:No data on Impala for flight GMI63HZ.
WARNING:root:No data on Impala for flight LLX5936.
WARNING:root:No data on Impala for flight GMI82CD.
WARNING:root:No data on Impala for flight GMI99YE.
WARNING:root:No data on Impala for flight GMI14SA.
WARNING:root:No data on Impala for flight GMI99AZ.
WARNING:root:No data on Impala for flight GMI17DG.
WARNING:root:No data on Impala for flight GMI32FG.
WARNING:root:No data on Impala for flight TUI2323.
WARNING:root:No data on Impala for flight GMI19YB.
WARNING:root:No data on Impala for flight GMI62YG.
WARNING:root:No data on Impala for flight TUI1FX.
WARNING:root:No data on Impala for flight CFG4WA.
WARNING:root:No data on Impala for flight CFG2YX.
WARNING:root:No data on Impala for flight TUI5CM.
WARNING:root:No data on Impala for flight CFG2MT.
WARNING:root:No data on Impala for flight TUI32F.
WARNING:root:No data on Impala for flight TUI21M.
WARNING:root:No data on Impala for flight TUI9XE.
WARNING:root:No data on Impala for flight TUI6515.
WARNING:root:No data on Impala for flight TUI5DH.
WARNING:root:No data on Impala for flight TUI7WC.
WARNING:root:No data on Impala for flight TUI2619.
WARNING:root:No data on Impala for flight BMW54.
WARNING:root:No data on Impala for flight TUI6503.
WARNING:root:No data on Impala for flight ARZ8336.
WARNING:root:No data on Impala for flight BAW54RT.
WARNING:root:No data on Impala for flight TUI58M.
WARNING:root:No data on Impala for flight EWG230.
WARNING:root:No data on Impala for flight EWG2UH.
WARNING:root:No data on Impala for flight EWG3ZA.
WARNING:root:No data on Impala for flight EWG8EW.
WARNING:root:No data on Impala for flight EWG91P.
WARNING:root:No data on Impala for flight EWG15A.
WARNING:root:No data on Impala for flight EWG7VC.
WARNING:root:No data on Impala for flight EWG9BL.
WARNING:root:No data on Impala for flight EWG8RG.
WARNING:root:No data on Impala for flight EWG2EJ.
WARNING:root:No data on Impala for flight TUI1TK.
WARNING:root:No data on Impala for flight EWG2YC.
WARNING:root:No data on Impala for flight EWG2VR.
WARNING:root:No data on Impala for flight EWG3GZ.
WARNING:root:No data on Impala for flight EWG6KR.
WARNING:root:No data on Impala for flight EWG8WT.
WARNING:root:No data on Impala for flight EWG5TR.
WARNING:root:No data on Impala for flight EWG7GL.
WARNING:root:No data on Impala for flight CFG7MA.
WARNING:root:No data on Impala for flight CFG4HF.
WARNING:root:No data on Impala for flight CFG2LV.
WARNING:root:No data on Impala for flight CFG8KA.
WARNING:root:No data on Impala for flight CFG5HC.
WARNING:root:No data on Impala for flight CFG8ME.
WARNING:root:No data on Impala for flight CFG5KT.
WARNING:root:No data on Impala for flight CFG293.
WARNING:root:No data on Impala for flight EWG4EU.
WARNING:root:No data on Impala for flight EWG8HZ.
WARNING:root:No data on Impala for flight EWG9580.
WARNING:root:No data on Impala for flight DLH572.
WARNING:root:No data on Impala for flight DLH6RW.
WARNING:root:No data on Impala for flight DLH1424.
WARNING:root:No data on Impala for flight DLH6KA.
WARNING:root:No data on Impala for flight EWG9581.
WARNING:root:No data on Impala for flight EWG4Z.
WARNING:root:No data on Impala for flight EWG82W.
WARNING:root:No data on Impala for flight EWG3EW.
WARNING:root:No data on Impala for flight EWG3RH.
WARNING:root:No data on Impala for flight EWG6CV.
WARNING:root:No data on Impala for flight GWI6906.
WARNING:root:No data on Impala for flight EWG3LR.
WARNING:root:No data on Impala for flight EWG6VU.
WARNING:root:No data on Impala for flight EWG7RZ.
WARNING:root:No data on Impala for flight EWG38A.
WARNING:root:No data on Impala for flight EWG7521.
WARNING:root:No data on Impala for flight EWG7BP.
WARNING:root:No data on Impala for flight EWG8MF.
WARNING:root:No data on Impala for flight AHO797W.
WARNING:root:No data on Impala for flight EWG3NR.
WARNING:root:No data on Impala for flight EWG9GK.
WARNING:root:No data on Impala for flight EWG8KK.
WARNING:root:No data on Impala for flight EWG582.
WARNING:root:No data on Impala for flight EWG9RC.
WARNING:root:No data on Impala for flight GMI12HJ.
WARNING:root:No data on Impala for flight EWG583.
WARNING:root:No data on Impala for flight EWG31J.
WARNING:root:No data on Impala for flight EWG5938.
WARNING:root:No data on Impala for flight EWG1NY.
WARNING:root:No data on Impala for flight EWG5EB.
WARNING:root:No data on Impala for flight EWG3MG.
WARNING:root:No data on Impala for flight EWG391.
WARNING:root:No data on Impala for flight EWG591.
WARNING:root:No data on Impala for flight AHO518U.
WARNING:root:No data on Impala for flight TUI48G.
WARNING:root:No data on Impala for flight CFG848.
WARNING:root:No data on Impala for flight CFG849.
WARNING:root:No data on Impala for flight CFG875.
WARNING:root:No data on Impala for flight CFG8AC.
WARNING:root:No data on Impala for flight DLH35X.
WARNING:root:No data on Impala for flight DLH88W.
WARNING:root:No data on Impala for flight DLH07X.
WARNING:root:No data on Impala for flight CFG1DY.
WARNING:root:No data on Impala for flight DLH44C.
WARNING:root:No data on Impala for flight DLH61U.
WARNING:root:No data on Impala for flight DLH91H.
WARNING:root:No data on Impala for flight CFG9KE.
WARNING:root:No data on Impala for flight DLH59H.
WARNING:root:No data on Impala for flight DLH51J.
WARNING:root:No data on Impala for flight DLH97E.
WARNING:root:No data on Impala for flight DLH53P.
WARNING:root:No data on Impala for flight DLH62Y.
WARNING:root:No data on Impala for flight DLH21P.
WARNING:root:No data on Impala for flight DLH4RW.
WARNING:root:No data on Impala for flight DLH87Y.
WARNING:root:No data on Impala for flight DLH9FY.
WARNING:root:No data on Impala for flight DLH77C.
WARNING:root:No data on Impala for flight DLH17N.
WARNING:root:No data on Impala for flight DLH2VV.
WARNING:root:No data on Impala for flight DLH88P.
WARNING:root:No data on Impala for flight EWG6K.
WARNING:root:No data on Impala for flight DLH37N.
WARNING:root:No data on Impala for flight EWG9PA.
WARNING:root:No data on Impala for flight DLH8RM.
WARNING:root:No data on Impala for flight EWG9UR.
WARNING:root:No data on Impala for flight DLH18X.
WARNING:root:No data on Impala for flight DLH72T.
WARNING:root:No data on Impala for flight EWG7AL.
WARNING:root:No data on Impala for flight EWG521.
WARNING:root:No data on Impala for flight DLH52X.
WARNING:root:No data on Impala for flight EWG520.
WARNING:root:No data on Impala for flight DLH55K.
WARNING:root:No data on Impala for flight EWG599.
WARNING:root:No data on Impala for flight EWG581.
WARNING:root:No data on Impala for flight EWG580.
WARNING:root:No data on Impala for flight DLH99P.
WARNING:root:No data on Impala for flight DLH05A.
WARNING:root:No data on Impala for flight DLH08X.
WARNING:root:No data on Impala for flight DLH03Y.
WARNING:root:No data on Impala for flight DLH68W.
WARNING:root:No data on Impala for flight DLH3CM.
WARNING:root:No data on Impala for flight DLH37F.
WARNING:root:No data on Impala for flight DLH01M.
WARNING:root:No data on Impala for flight DLH45N.
WARNING:root:No data on Impala for flight DLH19P.
WARNING:root:No data on Impala for flight DLH02A.
WARNING:root:No data on Impala for flight DLH75U.
WARNING:root:No data on Impala for flight DLH54M.
WARNING:root:No data on Impala for flight DLH1322.
WARNING:root:No data on Impala for flight DLH55E.
WARNING:root:No data on Impala for flight DLH1323.
WARNING:root:No data on Impala for flight DLH99X.
WARNING:root:No data on Impala for flight DLH1158.
WARNING:root:No data on Impala for flight DLH42K.
WARNING:root:No data on Impala for flight DLH05E.
WARNING:root:No data on Impala for flight DLH54C.
WARNING:root:No data on Impala for flight DLH6UV.
WARNING:root:No data on Impala for flight DLH85N.
WARNING:root:No data on Impala for flight DLH1159.
WARNING:root:No data on Impala for flight DLH1152.
WARNING:root:No data on Impala for flight DLH1153.
WARNING:root:No data on Impala for flight DLH2UX.
WARNING:root:No data on Impala for flight DLH1157.
WARNING:root:No data on Impala for flight DLH77P.
WARNING:root:No data on Impala for flight DLH336.
WARNING:root:No data on Impala for flight DLH44M.
WARNING:root:No data on Impala for flight DLH9CJ.
WARNING:root:No data on Impala for flight DLH98F.
WARNING:root:No data on Impala for flight DLH7MM.
WARNING:root:No data on Impala for flight DLH64U.
WARNING:root:No data on Impala for flight DLH9HP.
WARNING:root:No data on Impala for flight DLH5UW.
WARNING:root:No data on Impala for flight DLH3WJ.
WARNING:root:No data on Impala for flight DLH6KK.
WARNING:root:No data on Impala for flight DLH08Y.
WARNING:root:No data on Impala for flight DLH39X.
WARNING:root:No data on Impala for flight DLH28Y.
WARNING:root:No data on Impala for flight DLH52T.
WARNING:root:No data on Impala for flight DLH06K.
WARNING:root:No data on Impala for flight DLH1316.
WARNING:root:No data on Impala for flight EWG6GR.
WARNING:root:No data on Impala for flight DLH8CU.
WARNING:root:No data on Impala for flight DLH47E.
WARNING:root:No data on Impala for flight EWG1YF.
WARNING:root:No data on Impala for flight EWG7XA.
WARNING:root:No data on Impala for flight DLH49P.
WARNING:root:No data on Impala for flight EWG3VU.
WARNING:root:No data on Impala for flight DLH54N.
WARNING:root:No data on Impala for flight EWG1VT.
WARNING:root:No data on Impala for flight EWG5XC.
WARNING:root:No data on Impala for flight EFD3P.
WARNING:root:No data on Impala for flight BCS6824.
WARNING:root:No data on Impala for flight GEC8269.
WARNING:root:No data on Impala for flight BCS6823.
WARNING:root:No data on Impala for flight HHN20B.
WARNING:root:No data on Impala for flight DIMAH.
WARNING:root:No data on Impala for flight XGO2MV.
WARNING:root:No data on Impala for flight DCS705.
WARNING:root:No data on Impala for flight AHO726M.
WARNING:root:No data on Impala for flight ATL5B.
WARNING:root:No data on Impala for flight BAW559.
WARNING:root:No data on Impala for flight BAW633.
WARNING:root:No data on Impala for flight BAW59GT.
WARNING:root:No data on Impala for flight BAW82GR.
WARNING:root:No data on Impala for flight BAW66GA.
WARNING:root:No data on Impala for flight BAW64CF.
WARNING:root:No data on Impala for flight CLJ6325.
WARNING:root:No data on Impala for flight TCX1124.
WARNING:root:No data on Impala for flight TOM6WG.
WARNING:root:No data on Impala for flight TCX3HF.
WARNING:root:No data on Impala for flight BAW598D.
WARNING:root:No data on Impala for flight BAW61BA.
WARNING:root:No data on Impala for flight TCX7WG.
WARNING:root:No data on Impala for flight BAW2591.
WARNING:root:No data on Impala for flight BAW599.
WARNING:root:No data on Impala for flight BAW639.
WARNING:root:No data on Impala for flight BAW631.
WARNING:root:No data on Impala for flight BAW658.
WARNING:root:No data on Impala for flight BAW659.
WARNING:root:No data on Impala for flight EXS68L.
WARNING:root:No data on Impala for flight EXS36K.
WARNING:root:No data on Impala for flight BAW84ZV.
WARNING:root:No data on Impala for flight BAW585E.
WARNING:root:No data on Impala for flight BAW48G.
WARNING:root:No data on Impala for flight BAW2649.
WARNING:root:No data on Impala for flight BAW3RP.
WARNING:root:No data on Impala for flight BAW65PL.
WARNING:root:No data on Impala for flight BAW15PZ.
WARNING:root:No data on Impala for flight BAW579V.
WARNING:root:No data on Impala for flight BAW555.
WARNING:root:No data on Impala for flight BAW881V.
WARNING:root:No data on Impala for flight BAW604.
WARNING:root:No data on Impala for flight EZY34DV.
WARNING:root:No data on Impala for flight BAW609.
WARNING:root:No data on Impala for flight BAW605.
WARNING:root:No data on Impala for flight EZY25MR.
WARNING:root:No data on Impala for flight BAW34BQ.
WARNING:root:No data on Impala for flight BAW9WZ.
WARNING:root:No data on Impala for flight BAW557.
WARNING:root:No data on Impala for flight BAW542.
WARNING:root:No data on Impala for flight EZY79PR.
WARNING:root:No data on Impala for flight EZY96YD.
WARNING:root:No data on Impala for flight BAW545.
WARNING:root:No data on Impala for flight EXS81J.
WARNING:root:No data on Impala for flight EXS88C.
WARNING:root:No data on Impala for flight EZY36ZH.
WARNING:root:No data on Impala for flight EXS69H.
WARNING:root:No data on Impala for flight EZY59EG.
WARNING:root:No data on Impala for flight BAW53ZG.
WARNING:root:No data on Impala for flight EZY15PT.
WARNING:root:No data on Impala for flight BAW18VT.
WARNING:root:No data on Impala for flight EZY61LE.
WARNING:root:No data on Impala for flight EZY96HL.
WARNING:root:No data on Impala for flight EZY25AM.
WARNING:root:No data on Impala for flight EZY98XB.
WARNING:root:No data on Impala for flight EZY87YR.
WARNING:root:No data on Impala for flight BAW43LQ.
WARNING:root:No data on Impala for flight BAW544K.
WARNING:root:No data on Impala for flight EZY13QM.
WARNING:root:No data on Impala for flight BAW65TR.
WARNING:root:No data on Impala for flight EZY57JW.
WARNING:root:No data on Impala for flight GCEYL.
WARNING:root:No data on Impala for flight GRHMS.
WARNING:root:No data on Impala for flight EZY93UQ.
WARNING:root:No data on Impala for flight TOM6LY.
WARNING:root:No data on Impala for flight EZY58WQ.
WARNING:root:No data on Impala for flight EZY49WH.
WARNING:root:No data on Impala for flight EZY48PA.
WARNING:root:No data on Impala for flight EZY71VB.
WARNING:root:No data on Impala for flight BAW650.
WARNING:root:No data on Impala for flight EZY8072.
WARNING:root:No data on Impala for flight BAW651.
WARNING:root:No data on Impala for flight EZY27XG.
WARNING:root:No data on Impala for flight BAW256R.
WARNING:root:No data on Impala for flight EZY31CN.
WARNING:root:No data on Impala for flight TOM86V.
WARNING:root:No data on Impala for flight EZY59UF.
WARNING:root:No data on Impala for flight EZY97FB.
WARNING:root:No data on Impala for flight TOM6GK.
WARNING:root:No data on Impala for flight EZY64GM.
WARNING:root:No data on Impala for flight BAW71CU.
WARNING:root:No data on Impala for flight EXS695.
WARNING:root:No data on Impala for flight EXS96H.
WARNING:root:No data on Impala for flight BAW127E.
WARNING:root:No data on Impala for flight EZY72NK.
WARNING:root:No data on Impala for flight TOM6BV.
WARNING:root:No data on Impala for flight EZY17VX.
WARNING:root:No data on Impala for flight EZY51YE.
WARNING:root:No data on Impala for flight TOM736.
WARNING:root:No data on Impala for flight TOM1MB.
WARNING:root:No data on Impala for flight TOM46K.
WARNING:root:No data on Impala for flight EZY56JL.
WARNING:root:No data on Impala for flight EZY26KV.
WARNING:root:No data on Impala for flight EZY72YT.
WARNING:root:No data on Impala for flight EZY8062.
WARNING:root:No data on Impala for flight EZY74DG.
WARNING:root:No data on Impala for flight EZY95KU.
WARNING:root:No data on Impala for flight TOM2XE.
WARNING:root:No data on Impala for flight TOM84E.
WARNING:root:No data on Impala for flight TOM32T.
WARNING:root:No data on Impala for flight TOM9MH.
WARNING:root:No data on Impala for flight EXS33W.
WARNING:root:No data on Impala for flight TCX7NG.
WARNING:root:No data on Impala for flight EZY26PD.
WARNING:root:No data on Impala for flight EZY38XB.
WARNING:root:No data on Impala for flight EZY807U.
WARNING:root:No data on Impala for flight BAW843R.
WARNING:root:No data on Impala for flight BAW842P.
WARNING:root:No data on Impala for flight EZY35XQ.
WARNING:root:No data on Impala for flight EZY319P.
WARNING:root:No data on Impala for flight TCX702.
WARNING:root:No data on Impala for flight EZY95HV.
WARNING:root:No data on Impala for flight TCX430.
WARNING:root:No data on Impala for flight TCX108.
WARNING:root:No data on Impala for flight TOM5JW.
WARNING:root:No data on Impala for flight BAW2557.
WARNING:root:No data on Impala for flight BAW661.
WARNING:root:No data on Impala for flight BAW3KG.
WARNING:root:No data on Impala for flight BAW77PL.
WARNING:root:No data on Impala for flight BAW79PL.
WARNING:root:No data on Impala for flight BAW58GV.
WARNING:root:No data on Impala for flight BAW205E.
WARNING:root:No data on Impala for flight BAW2677.
WARNING:root:No data on Impala for flight BAW2640.
WARNING:root:No data on Impala for flight BAW50MJ.
WARNING:root:No data on Impala for flight BAW2641.
WARNING:root:No data on Impala for flight TCX1107.
WARNING:root:No data on Impala for flight TCX1106.
WARNING:root:No data on Impala for flight TCX114.
WARNING:root:No data on Impala for flight TCX1KU.
WARNING:root:No data on Impala for flight BAW132.
WARNING:root:No data on Impala for flight EZY19QP.
WARNING:root:No data on Impala for flight EZY63RK.
WARNING:root:No data on Impala for flight EZY85PZ.
WARNING:root:No data on Impala for flight EZY49GN.
WARNING:root:No data on Impala for flight EZY54UC.
WARNING:root:No data on Impala for flight IBK2525.
WARNING:root:No data on Impala for flight TCX9FY.
WARNING:root:No data on Impala for flight TCX1V.
WARNING:root:No data on Impala for flight BAW154.
WARNING:root:No data on Impala for flight EXS99VN.
WARNING:root:No data on Impala for flight EXS22EF.
WARNING:root:No data on Impala for flight EXS48P.
WARNING:root:No data on Impala for flight EXS1262.
WARNING:root:No data on Impala for flight EXS64C.
WARNING:root:No data on Impala for flight EXS12PK.
WARNING:root:No data on Impala for flight EXS61AB.
WARNING:root:No data on Impala for flight EZY17ED.
WARNING:root:No data on Impala for flight EZY89KC.
WARNING:root:No data on Impala for flight EXS64W.
WARNING:root:No data on Impala for flight EZY24UT.
WARNING:root:No data on Impala for flight TOM313.
WARNING:root:No data on Impala for flight WZZ6738.
WARNING:root:No data on Impala for flight EZY24DP.
WARNING:root:No data on Impala for flight EZY32TR.
WARNING:root:No data on Impala for flight EZY26UE.
WARNING:root:No data on Impala for flight EZY12UH.
WARNING:root:No data on Impala for flight EXS77CK.
WARNING:root:No data on Impala for flight EZY67DE.
WARNING:root:No data on Impala for flight EXS1678.
WARNING:root:No data on Impala for flight VPCSK.
WARNING:root:No data on Impala for flight CFE79DW.
WARNING:root:No data on Impala for flight SBI3071.
WARNING:root:No data on Impala for flight AFL2500.
WARNING:root:No data on Impala for flight AFL2603.
WARNING:root:No data on Impala for flight VPCIG.
WARNING:root:No data on Impala for flight AFL2602.
WARNING:root:No data on Impala for flight AFL2606.
WARNING:root:No data on Impala for flight AFL2604.
WARNING:root:No data on Impala for flight AFL2620.
WARNING:root:No data on Impala for flight AFL2501.
WARNING:root:No data on Impala for flight SDM6701.
WARNING:root:No data on Impala for flight GMI66WA.
WARNING:root:No data on Impala for flight PBD878.
WARNING:root:No data on Impala for flight EZY28LB.
WARNING:root:No data on Impala for flight EZY12VJ.
WARNING:root:No data on Impala for flight EZY24AX.
WARNING:root:No data on Impala for flight AUA417C.
WARNING:root:No data on Impala for flight EZY35RV.
WARNING:root:No data on Impala for flight FOO1001.
WARNING:root:No data on Impala for flight EZY13KH.
WARNING:root:No data on Impala for flight EZY64HB.
WARNING:root:No data on Impala for flight EZY12EJ.
WARNING:root:No data on Impala for flight AUA427.
WARNING:root:No data on Impala for flight EZY32EN.
WARNING:root:No data on Impala for flight EZY85GE.
WARNING:root:No data on Impala for flight EZY28CD.
WARNING:root:No data on Impala for flight EZY58TR.
WARNING:root:No data on Impala for flight EZY48HB.
WARNING:root:No data on Impala for flight LDM103.
WARNING:root:No data on Impala for flight LDM71A.
WARNING:root:No data on Impala for flight LDM118.
WARNING:root:No data on Impala for flight EZY3891.
WARNING:root:No data on Impala for flight EZY45XA.
WARNING:root:No data on Impala for flight EZY168Y.
WARNING:root:No data on Impala for flight LDM109.
WARNING:root:No data on Impala for flight EZY89WP.
WARNING:root:No data on Impala for flight EZY23ZB.
WARNING:root:No data on Impala for flight LDM110.
WARNING:root:No data on Impala for flight EZY3797.
WARNING:root:No data on Impala for flight EZY68DX.
WARNING:root:No data on Impala for flight EZY14HN.
WARNING:root:No data on Impala for flight EZY85ZE.
WARNING:root:No data on Impala for flight EZY39PJ.
WARNING:root:No data on Impala for flight EZY36CX.
WARNING:root:No data on Impala for flight EZY403R.
WARNING:root:No data on Impala for flight EZY79HE.
WARNING:root:No data on Impala for flight EZY34TM.
WARNING:root:No data on Impala for flight EZY53JP.
WARNING:root:No data on Impala for flight EZY47DP.
WARNING:root:No data on Impala for flight EZY72UF.
WARNING:root:No data on Impala for flight EZY4207.
WARNING:root:No data on Impala for flight EZY95ME.
WARNING:root:No data on Impala for flight EZY79MU.
WARNING:root:No data on Impala for flight EZY32RJ.
WARNING:root:No data on Impala for flight AUA415C.
WARNING:root:No data on Impala for flight EZY63EP.
WARNING:root:No data on Impala for flight EZY59JC.
WARNING:root:No data on Impala for flight EZY78ZE.
WARNING:root:No data on Impala for flight AUA414.
WARNING:root:No data on Impala for flight EZY48QE.
WARNING:root:No data on Impala for flight EZY42RN.
WARNING:root:No data on Impala for flight EZY39DR.
WARNING:root:No data on Impala for flight EWG5889.
WARNING:root:No data on Impala for flight GAC134D.
WARNING:root:No data on Impala for flight EZY78ED.
WARNING:root:No data on Impala for flight EZY13XP.
WARNING:root:No data on Impala for flight EZY168D.
WARNING:root:No data on Impala for flight EZY94XF.
WARNING:root:No data on Impala for flight EZY69ML.
WARNING:root:No data on Impala for flight EZY97QR.
WARNING:root:No data on Impala for flight EZY27NC.
WARNING:root:No data on Impala for flight AUA96LU.
WARNING:root:No data on Impala for flight EZY27JF.
WARNING:root:No data on Impala for flight EZY58YM.
WARNING:root:No data on Impala for flight EZY78CT.
WARNING:root:No data on Impala for flight EWG9ZX.
WARNING:root:No data on Impala for flight EWG6808.
WARNING:root:No data on Impala for flight EWG4YA.
WARNING:root:No data on Impala for flight EWG6860.
WARNING:root:No data on Impala for flight EZY3737.
WARNING:root:No data on Impala for flight EWG6850.
WARNING:root:No data on Impala for flight LDM150.
WARNING:root:No data on Impala for flight EZY3738.
WARNING:root:No data on Impala for flight LDM101.
WARNING:root:No data on Impala for flight LDM151.
WARNING:root:No data on Impala for flight LDM102.
WARNING:root:No data on Impala for flight LDM119.
WARNING:root:No data on Impala for flight LDM120.
WARNING:root:No data on Impala for flight EZY539C.
WARNING:root:No data on Impala for flight AAB405.
WARNING:root:No data on Impala for flight JAF1CP.
WARNING:root:No data on Impala for flight JAF14X.
WARNING:root:No data on Impala for flight JAF32A.
WARNING:root:No data on Impala for flight JAF3HL.
WARNING:root:No data on Impala for flight OOPRM.
WARNING:root:No data on Impala for flight BEL371.
WARNING:root:No data on Impala for flight BEL68E.
WARNING:root:No data on Impala for flight JAF93K.
WARNING:root:No data on Impala for flight BEL3325.
WARNING:root:No data on Impala for flight BEL3107.
WARNING:root:No data on Impala for flight BEL6CE.
WARNING:root:No data on Impala for flight BEL3108.
WARNING:root:No data on Impala for flight BEL3370.
WARNING:root:No data on Impala for flight BEL3885.
WARNING:root:No data on Impala for flight BEL3766.
WARNING:root:No data on Impala for flight BEL3272.
WARNING:root:No data on Impala for flight BEL75Y.
WARNING:root:No data on Impala for flight BEL5FC.
WARNING:root:No data on Impala for flight JAF9GL.
WARNING:root:No data on Impala for flight BEL76F.
WARNING:root:No data on Impala for flight BEL36V.
WARNING:root:No data on Impala for flight BEL9LR.
WARNING:root:No data on Impala for flight BEL3136.
WARNING:root:No data on Impala for flight BEL8NB.
WARNING:root:No data on Impala for flight BEL14Q.
WARNING:root:No data on Impala for flight BEL3616.
WARNING:root:No data on Impala for flight BEL54X.
WARNING:root:No data on Impala for flight BEL3577.
WARNING:root:No data on Impala for flight BEL7MR.
WARNING:root:No data on Impala for flight BEL88F.
WARNING:root:No data on Impala for flight BEL31P.
WARNING:root:No data on Impala for flight BEL22N.
WARNING:root:No data on Impala for flight BEL10X.
WARNING:root:No data on Impala for flight BEL3623.
WARNING:root:No data on Impala for flight BEL81Z.
WARNING:root:No data on Impala for flight BEL9NA.
WARNING:root:No data on Impala for flight BEL5HR.
WARNING:root:No data on Impala for flight BEL3881.
WARNING:root:No data on Impala for flight BEL43D.
WARNING:root:No data on Impala for flight BEL82F.
WARNING:root:No data on Impala for flight JAF66D.
WARNING:root:No data on Impala for flight JAF38A.
WARNING:root:No data on Impala for flight BEL3882.
WARNING:root:No data on Impala for flight JAF3924.
WARNING:root:No data on Impala for flight LZB432.
WARNING:root:No data on Impala for flight LZB407.
WARNING:root:No data on Impala for flight LZB408.
WARNING:root:No data on Impala for flight LZB851.
WARNING:root:No data on Impala for flight LZB431.
WARNING:root:No data on Impala for flight SAS775.
WARNING:root:No data on Impala for flight SAS776.
WARNING:root:No data on Impala for flight SAS2588.
WARNING:root:No data on Impala for flight SAS792.
WARNING:root:No data on Impala for flight SAS2555.
WARNING:root:No data on Impala for flight DTR636.
WARNING:root:No data on Impala for flight SAS791.
WARNING:root:No data on Impala for flight DTR635.
WARNING:root:No data on Impala for flight CSA700.
WARNING:root:No data on Impala for flight SRR6381.
WARNING:root:No data on Impala for flight AEE615.
WARNING:root:No data on Impala for flight CSA701.
WARNING:root:No data on Impala for flight AEE4CA.
WARNING:root:No data on Impala for flight AEE5CD.
WARNING:root:No data on Impala for flight AEE61PG.
WARNING:root:No data on Impala for flight AEE61CG.
WARNING:root:No data on Impala for flight AEE3NC.
WARNING:root:No data on Impala for flight AEE618.
WARNING:root:No data on Impala for flight AEE601.
WARNING:root:No data on Impala for flight AEE3DW.
WARNING:root:No data on Impala for flight AEE2FL.
WARNING:root:No data on Impala for flight AEE6AV.
WARNING:root:No data on Impala for flight WZZ619.
WARNING:root:No data on Impala for flight WZZ867.
WARNING:root:No data on Impala for flight AEE2EG.
WARNING:root:No data on Impala for flight WZZ433.
WARNING:root:No data on Impala for flight SAS4823.
WARNING:root:No data on Impala for flight SAS4824.
WARNING:root:No data on Impala for flight NAX2GY.
WARNING:root:No data on Impala for flight NAX3YO.
WARNING:root:No data on Impala for flight NAX1HD.
WARNING:root:No data on Impala for flight SAS1816.
WARNING:root:No data on Impala for flight NAX21B.
WARNING:root:No data on Impala for flight NAX7JP.
WARNING:root:No data on Impala for flight NAX6JS.
WARNING:root:No data on Impala for flight NAX42N.
WARNING:root:No data on Impala for flight NAX4VC.
WARNING:root:No data on Impala for flight NAX13PT.
WARNING:root:No data on Impala for flight NAX3CX.
WARNING:root:No data on Impala for flight NAX14VN.
WARNING:root:No data on Impala for flight NAX5VD.
WARNING:root:No data on Impala for flight NAX3YL.
WARNING:root:No data on Impala for flight NAX1KB.
WARNING:root:No data on Impala for flight NAX37N.
WARNING:root:No data on Impala for flight NAX2ZY.
WARNING:root:No data on Impala for flight NAX47E.
WARNING:root:No data on Impala for flight NAX6LK.
WARNING:root:No data on Impala for flight NAX3NG.
WARNING:root:No data on Impala for flight NAX2WZ.
WARNING:root:No data on Impala for flight SAS793.
WARNING:root:No data on Impala for flight SAS74E.
WARNING:root:No data on Impala for flight SAS53P.
WARNING:root:No data on Impala for flight TRA16J.
WARNING:root:No data on Impala for flight KLM39S.
WARNING:root:No data on Impala for flight KLM1258.
WARNING:root:No data on Impala for flight KLM69M.
WARNING:root:No data on Impala for flight KLM33T.
WARNING:root:No data on Impala for flight TRA421U.
WARNING:root:No data on Impala for flight KLM78Q.
WARNING:root:No data on Impala for flight KLM1596.
WARNING:root:No data on Impala for flight TRA18U.
WARNING:root:No data on Impala for flight TRA46K.
WARNING:root:No data on Impala for flight TRA47W.
WARNING:root:No data on Impala for flight KLM1598.
WARNING:root:No data on Impala for flight TRA70X.
WARNING:root:No data on Impala for flight TRA9Y.
WARNING:root:No data on Impala for flight KLM591.
WARNING:root:No data on Impala for flight KLM103.
WARNING:root:No data on Impala for flight KLM1630.
WARNING:root:No data on Impala for flight TRA93U.
WARNING:root:No data on Impala for flight KLM1253.
WARNING:root:No data on Impala for flight TRA84P.
WARNING:root:No data on Impala for flight KLM48C.
WARNING:root:No data on Impala for flight KLM81K.
WARNING:root:No data on Impala for flight TRA54U.
WARNING:root:No data on Impala for flight CND113.
WARNING:root:No data on Impala for flight CND114.
WARNING:root:No data on Impala for flight KLM1592.
WARNING:root:No data on Impala for flight TRA71H.
WARNING:root:No data on Impala for flight TRA77N.
WARNING:root:No data on Impala for flight KLM1567.
WARNING:root:No data on Impala for flight KLM66V.
WARNING:root:No data on Impala for flight ENT7129.
WARNING:root:No data on Impala for flight KLM24H.
WARNING:root:No data on Impala for flight TRA1626.
WARNING:root:No data on Impala for flight ENT7128.
WARNING:root:No data on Impala for flight ENT438.
WARNING:root:No data on Impala for flight ENT7366.
WARNING:root:No data on Impala for flight ENT437.
WARNING:root:No data on Impala for flight LLX5431.
WARNING:root:No data on Impala for flight ENT778.
WARNING:root:No data on Impala for flight LLX5432.
WARNING:root:No data on Impala for flight LLX5433.
WARNING:root:No data on Impala for flight LLP342A.
WARNING:root:No data on Impala for flight LLP6135.
WARNING:root:No data on Impala for flight LOT437.
WARNING:root:No data on Impala for flight NJE520P.
WARNING:root:No data on Impala for flight TAP551.
WARNING:root:No data on Impala for flight LOT433.
WARNING:root:No data on Impala for flight NJE909R.
WARNING:root:No data on Impala for flight TAP1305.
WARNING:root:No data on Impala for flight TAP557J.
WARNING:root:No data on Impala for flight TAP1272.
WARNING:root:No data on Impala for flight HFY312P.
WARNING:root:No data on Impala for flight TAP1273.
WARNING:root:No data on Impala for flight TAP1312.
WARNING:root:No data on Impala for flight TAP1274.
WARNING:root:No data on Impala for flight TAP1235.
WARNING:root:No data on Impala for flight TAP553.
WARNING:root:No data on Impala for flight TAP573.
WARNING:root:No data on Impala for flight TVS2799.
WARNING:root:No data on Impala for flight CSA5DE.
WARNING:root:No data on Impala for flight CSA5DF.
WARNING:root:No data on Impala for flight TAP1262.
WARNING:root:No data on Impala for flight AIZ746.
WARNING:root:No data on Impala for flight AIZ745.
WARNING:root:No data on Impala for flight TVS2437.
WARNING:root:No data on Impala for flight TVS2452.
WARNING:root:No data on Impala for flight TVS2436.
WARNING:root:No data on Impala for flight TVS2453.
WARNING:root:No data on Impala for flight TVS6X.
WARNING:root:No data on Impala for flight ROT381H.
WARNING:root:No data on Impala for flight ROT382W.
WARNING:root:No data on Impala for flight BMS2HX.
WARNING:root:No data on Impala for flight ROT383R.
WARNING:root:No data on Impala for flight BMS5516.
WARNING:root:No data on Impala for flight ADR323.
WARNING:root:No data on Impala for flight ADR322.
WARNING:root:No data on Impala for flight ADR342.
WARNING:root:No data on Impala for flight CND516.
WARNING:root:No data on Impala for flight SAS4704.
WARNING:root:No data on Impala for flight BLX426.
WARNING:root:No data on Impala for flight BLX425.
WARNING:root:No data on Impala for flight SAS4703.
WARNING:root:No data on Impala for flight BLX735.
WARNING:root:No data on Impala for flight BLX553.
WARNING:root:No data on Impala for flight HBJGP.
WARNING:root:No data on Impala for flight BCS7079.
WARNING:root:No data on Impala for flight SAS67W.
WARNING:root:No data on Impala for flight SAS2806.
WARNING:root:No data on Impala for flight PGT38L.
WARNING:root:No data on Impala for flight THY1MP.
WARNING:root:No data on Impala for flight PGT93J.
WARNING:root:No data on Impala for flight KKK2EY.
WARNING:root:No data on Impala for flight THY78C.
WARNING:root:No data on Impala for flight THY9PG.
WARNING:root:No data on Impala for flight THY6.
WARNING:root:No data on Impala for flight THY6DC.
WARNING:root:No data on Impala for flight THY75Z.
WARNING:root:No data on Impala for flight THY12.
WARNING:root:No data on Impala for flight THY4QM.
WARNING:root:No data on Impala for flight THY4QR.
WARNING:root:No data on Impala for flight THY183.
WARNING:root:No data on Impala for flight THY82M.
WARNING:root:No data on Impala for flight THY36.
WARNING:root:No data on Impala for flight THY9SC.
WARNING:root:No data on Impala for flight THY7WR.
WARNING:root:No data on Impala for flight THY6DG.
WARNING:root:No data on Impala for flight THY8.
WARNING:root:No data on Impala for flight THY2.
WARNING:root:No data on Impala for flight THY2FM.
WARNING:root:No data on Impala for flight THY2AS.
WARNING:root:No data on Impala for flight THY34.
WARNING:root:No data on Impala for flight MNB351.
WARNING:root:No data on Impala for flight PGT89P.
WARNING:root:No data on Impala for flight TWI782.
WARNING:root:No data on Impala for flight PGT75K.
WARNING:root:No data on Impala for flight ASL16W.
WARNING:root:No data on Impala for flight ASL68Q.
WARNING:root:No data on Impala for flight FCB326.
WARNING:root:No data on Impala for flight ASL43Y.
WARNING:root:No data on Impala for flight FCB658.
WARNING:root:No data on Impala for flight FCB682.
WARNING:root:No data on Impala for flight ASL98F.
WARNING:root:No data on Impala for flight FCB379.
WARNING:root:No data on Impala for flight TVS5GJ.
WARNING:root:No data on Impala for flight FCB327.
WARNING:root:No data on Impala for flight EIN40X.
WARNING:root:No data on Impala for flight RYR88CW.
WARNING:root:No data on Impala for flight RYR45JM.
WARNING:root:No data on Impala for flight RYR2581.
WARNING:root:No data on Impala for flight RYR31CR.
WARNING:root:No data on Impala for flight RYR79PA.
WARNING:root:No data on Impala for flight RYR30VA.
WARNING:root:No data on Impala for flight RYR47ZP.
WARNING:root:No data on Impala for flight RYR604W.
WARNING:root:No data on Impala for flight RYR31KY.
WARNING:root:No data on Impala for flight RYR27XL.
WARNING:root:No data on Impala for flight RYR31HZ.
WARNING:root:No data on Impala for flight RYR90GF.
WARNING:root:No data on Impala for flight RYR986A.
WARNING:root:No data on Impala for flight RYR5604.
WARNING:root:No data on Impala for flight RYR67CH.
WARNING:root:No data on Impala for flight RYR17XT.
WARNING:root:No data on Impala for flight RYR76WB.
WARNING:root:No data on Impala for flight RYR300P.
WARNING:root:No data on Impala for flight RYR843H.
WARNING:root:No data on Impala for flight RYR16MJ.
WARNING:root:No data on Impala for flight RYR8414.
WARNING:root:No data on Impala for flight EIN451.
WARNING:root:No data on Impala for flight EIN416.
WARNING:root:No data on Impala for flight RYR7211.
WARNING:root:No data on Impala for flight RYR79ZR.
WARNING:root:No data on Impala for flight RYR87LL.
WARNING:root:No data on Impala for flight RYR71BQ.
WARNING:root:No data on Impala for flight RYR30HG.
WARNING:root:No data on Impala for flight RYR218H.
WARNING:root:No data on Impala for flight RYR94FT.
WARNING:root:No data on Impala for flight RYR143F.
WARNING:root:No data on Impala for flight RYR98RM.
WARNING:root:No data on Impala for flight RYR248Z.
WARNING:root:No data on Impala for flight RYR70ZG.
WARNING:root:No data on Impala for flight RYR3Z.
WARNING:root:No data on Impala for flight RYR69VB.
WARNING:root:No data on Impala for flight RYR1911.
WARNING:root:No data on Impala for flight RYR52TK.
WARNING:root:No data on Impala for flight RYR829J.
WARNING:root:No data on Impala for flight RYS3405.
WARNING:root:No data on Impala for flight RYR2765.
WARNING:root:No data on Impala for flight RYR3746.
WARNING:root:No data on Impala for flight RYR60AU.
WARNING:root:No data on Impala for flight RYR8809.
WARNING:root:No data on Impala for flight RYR263C.
WARNING:root:No data on Impala for flight RYR438V.
WARNING:root:No data on Impala for flight RYR175R.
WARNING:root:No data on Impala for flight RYR83HB.
WARNING:root:No data on Impala for flight LDM663.
WARNING:root:No data on Impala for flight RYR87WH.
WARNING:root:No data on Impala for flight RYR73FZ.
WARNING:root:No data on Impala for flight LDM669.
WARNING:root:No data on Impala for flight LDM20A.
WARNING:root:No data on Impala for flight IBK2UM.
WARNING:root:No data on Impala for flight IBK5GR.
WARNING:root:No data on Impala for flight LDM303.
WARNING:root:No data on Impala for flight IBK6693.
WARNING:root:No data on Impala for flight IBK5602.
WARNING:root:No data on Impala for flight RYR18GT.
WARNING:root:No data on Impala for flight IBK1RG.
WARNING:root:No data on Impala for flight IBK6687.
WARNING:root:No data on Impala for flight RYR4W.
WARNING:root:No data on Impala for flight IBK6686.
WARNING:root:No data on Impala for flight IBK1023.
WARNING:root:No data on Impala for flight IBK9RU.
WARNING:root:No data on Impala for flight LDM665.
WARNING:root:No data on Impala for flight IBK5621.
WARNING:root:No data on Impala for flight IBK6LE.
WARNING:root:No data on Impala for flight IBK1021.
WARNING:root:No data on Impala for flight RYR20WP.
WARNING:root:No data on Impala for flight RYR51DP.
WARNING:root:No data on Impala for flight RYR22KL.
WARNING:root:No data on Impala for flight RYR675R.
WARNING:root:No data on Impala for flight RYR79VD.
WARNING:root:No data on Impala for flight RYR89JH.
WARNING:root:No data on Impala for flight IBK5106.
WARNING:root:No data on Impala for flight RYR29QL.
WARNING:root:No data on Impala for flight RYR952P.
WARNING:root:No data on Impala for flight RYR1069.
WARNING:root:No data on Impala for flight RYR233Y.
WARNING:root:No data on Impala for flight RYR2744.
WARNING:root:No data on Impala for flight RYR739D.
WARNING:root:No data on Impala for flight IBK4CT.
WARNING:root:No data on Impala for flight IBK538.
WARNING:root:No data on Impala for flight IBK5402.
WARNING:root:No data on Impala for flight RYR39PH.
WARNING:root:No data on Impala for flight RYR16QG.
WARNING:root:No data on Impala for flight RYR1M.
WARNING:root:No data on Impala for flight RYR59DW.
WARNING:root:No data on Impala for flight RYR588J.
WARNING:root:No data on Impala for flight RYR1888.
WARNING:root:No data on Impala for flight RYR5184.
WARNING:root:No data on Impala for flight RYR97WG.
WARNING:root:No data on Impala for flight RYR59JT.
WARNING:root:No data on Impala for flight RYR81HY.
WARNING:root:No data on Impala for flight IBK3NU.
WARNING:root:No data on Impala for flight RYR17UU.
WARNING:root:No data on Impala for flight IBK2MC.
WARNING:root:No data on Impala for flight RYR32BR.
WARNING:root:No data on Impala for flight LDM32.
WARNING:root:No data on Impala for flight RYR9102.
WARNING:root:No data on Impala for flight RYR47DU.
WARNING:root:No data on Impala for flight LDM33.
WARNING:root:No data on Impala for flight RYR55NF.
WARNING:root:No data on Impala for flight RYR25EF.
WARNING:root:No data on Impala for flight RYR28BB.
WARNING:root:No data on Impala for flight RYR40RY.
WARNING:root:No data on Impala for flight RYR90XD.
WARNING:root:No data on Impala for flight AZA108.
WARNING:root:No data on Impala for flight IBK3641.
WARNING:root:No data on Impala for flight EIN42K.
WARNING:root:No data on Impala for flight IBK56V.
WARNING:root:No data on Impala for flight IBK365L.
WARNING:root:No data on Impala for flight IBK3640.
WARNING:root:No data on Impala for flight RYR103U.
WARNING:root:No data on Impala for flight RYR63VF.
WARNING:root:No data on Impala for flight RYR4252.
WARNING:root:No data on Impala for flight IBK9549.
WARNING:root:No data on Impala for flight IBK64N.
WARNING:root:No data on Impala for flight RYR411T.
WARNING:root:No data on Impala for flight RYR65XX.
WARNING:root:No data on Impala for flight RYR715.
WARNING:root:No data on Impala for flight RYR27ZZ.
WARNING:root:No data on Impala for flight RYR34UU.
WARNING:root:No data on Impala for flight RYR52BD.
WARNING:root:No data on Impala for flight RYR380N.
WARNING:root:No data on Impala for flight RYR6K.
WARNING:root:No data on Impala for flight RYR70WM.
WARNING:root:No data on Impala for flight RYR93VT.
WARNING:root:No data on Impala for flight AZA324.
WARNING:root:No data on Impala for flight RYR832X.
WARNING:root:No data on Impala for flight AZA97U.
WARNING:root:No data on Impala for flight RYR639V.
WARNING:root:No data on Impala for flight EIN40W.
WARNING:root:No data on Impala for flight RYR91WG.
WARNING:root:No data on Impala for flight RYR78SK.
WARNING:root:No data on Impala for flight RYR8W.
WARNING:root:No data on Impala for flight RYR79SV.
WARNING:root:No data on Impala for flight LDM315.
WARNING:root:No data on Impala for flight RYR15DG.
WARNING:root:No data on Impala for flight IBK3668.
WARNING:root:No data on Impala for flight RYR705U.
WARNING:root:No data on Impala for flight RYR85NN.
WARNING:root:No data on Impala for flight RYR58LW.
WARNING:root:No data on Impala for flight RYR87BG.
WARNING:root:No data on Impala for flight IBK36FS.
WARNING:root:No data on Impala for flight RYR96SL.
WARNING:root:No data on Impala for flight RYR137W.
WARNING:root:No data on Impala for flight RYR159.
WARNING:root:No data on Impala for flight RYR559F.
WARNING:root:No data on Impala for flight RYR40NF.
WARNING:root:No data on Impala for flight RYR51FH.
WARNING:root:No data on Impala for flight AZA20Y.
WARNING:root:No data on Impala for flight LDM89.
WARNING:root:No data on Impala for flight RYR9R.
WARNING:root:No data on Impala for flight AZA156.
WARNING:root:No data on Impala for flight RYR38GV.
WARNING:root:No data on Impala for flight RYR4561.
WARNING:root:No data on Impala for flight RYR63SJ.
WARNING:root:No data on Impala for flight RYR347U.
WARNING:root:No data on Impala for flight RYR85VQ.
WARNING:root:No data on Impala for flight IBK6622.
WARNING:root:No data on Impala for flight RYR51HH.
WARNING:root:No data on Impala for flight IBK9463.
WARNING:root:No data on Impala for flight IBK6651.
WARNING:root:No data on Impala for flight EIN428.
WARNING:root:No data on Impala for flight IBK6RE.
WARNING:root:No data on Impala for flight IBK6505.
WARNING:root:No data on Impala for flight RYR3493.
WARNING:root:No data on Impala for flight RYR73FM.
WARNING:root:No data on Impala for flight RYR17CD.
WARNING:root:No data on Impala for flight RYR21LP.
WARNING:root:No data on Impala for flight RYR58JR.
WARNING:root:No data on Impala for flight RYR14RG.
WARNING:root:No data on Impala for flight RYR209H.
WARNING:root:No data on Impala for flight RYR87LT.
WARNING:root:No data on Impala for flight RYR632M.
WARNING:root:No data on Impala for flight RYR72AZ.
WARNING:root:No data on Impala for flight RYR42JK.
WARNING:root:No data on Impala for flight RYR67SZ.
WARNING:root:No data on Impala for flight RYR26WE.
WARNING:root:No data on Impala for flight RYR589C.
WARNING:root:No data on Impala for flight RYR758E.
WARNING:root:No data on Impala for flight LDM316.
WARNING:root:No data on Impala for flight RYR39XC.
WARNING:root:No data on Impala for flight AZA420.
WARNING:root:No data on Impala for flight RYR33SJ.
WARNING:root:No data on Impala for flight AZA403.
WARNING:root:No data on Impala for flight RYR730M.
WARNING:root:No data on Impala for flight LDM141.
WARNING:root:No data on Impala for flight AZA31Z.
WARNING:root:No data on Impala for flight RYR76HN.
WARNING:root:No data on Impala for flight RYR74SK.
WARNING:root:No data on Impala for flight RYR95JQ.
WARNING:root:No data on Impala for flight RYR20JY.
WARNING:root:No data on Impala for flight RYR3475.
WARNING:root:No data on Impala for flight RYR2956.
WARNING:root:No data on Impala for flight RYR79PW.
WARNING:root:No data on Impala for flight RYR88EX.
WARNING:root:No data on Impala for flight RYR63BY.
WARNING:root:No data on Impala for flight RYR789Z.
WARNING:root:No data on Impala for flight RYR9382.
WARNING:root:No data on Impala for flight RYR95WD.
WARNING:root:No data on Impala for flight RYR98TM.
WARNING:root:No data on Impala for flight RYR98EN.
WARNING:root:No data on Impala for flight RYR39RH.
WARNING:root:No data on Impala for flight RYR186K.
WARNING:root:No data on Impala for flight LDM522.
WARNING:root:No data on Impala for flight RYR18MQ.
WARNING:root:No data on Impala for flight LDM524.
WARNING:root:No data on Impala for flight LDM523.
WARNING:root:No data on Impala for flight RYR61WL.
WARNING:root:No data on Impala for flight RYR6121.
WARNING:root:No data on Impala for flight LDM525.
WARNING:root:No data on Impala for flight RYR95CT.
WARNING:root:No data on Impala for flight RYR54EK.
WARNING:root:No data on Impala for flight RYR42CT.
WARNING:root:No data on Impala for flight RYR2497.
WARNING:root:No data on Impala for flight RYR50LY.
WARNING:root:No data on Impala for flight RYR129Y.
WARNING:root:No data on Impala for flight RYR3748.
WARNING:root:No data on Impala for flight RYR34FY.
WARNING:root:No data on Impala for flight RYR75HU.
WARNING:root:No data on Impala for flight RYR31VL.
WARNING:root:No data on Impala for flight RYR74WK.
WARNING:root:No data on Impala for flight RYR720C.
WARNING:root:No data on Impala for flight RYR99UD.
WARNING:root:No data on Impala for flight RYR71CL.
WARNING:root:No data on Impala for flight RYR21UX.
WARNING:root:No data on Impala for flight RYR12PU.
WARNING:root:No data on Impala for flight IBK5FL.
WARNING:root:No data on Impala for flight IBK4MD.
WARNING:root:No data on Impala for flight IBK9461.
WARNING:root:No data on Impala for flight IBK6UK.
WARNING:root:No data on Impala for flight IBK7VR.
WARNING:root:No data on Impala for flight RYR83DL.
WARNING:root:No data on Impala for flight RYR98XZ.
WARNING:root:No data on Impala for flight RYR1AG.
WARNING:root:No data on Impala for flight IBK9460.
WARNING:root:No data on Impala for flight RYR14EB.
WARNING:root:No data on Impala for flight BEL64F.
WARNING:root:No data on Impala for flight RYR94JF.
WARNING:root:No data on Impala for flight LGL6556.
WARNING:root:No data on Impala for flight IBK514.
WARNING:root:No data on Impala for flight ACP2623.
WARNING:root:No data on Impala for flight LGL65R.
WARNING:root:No data on Impala for flight LGL8255.
WARNING:root:No data on Impala for flight LGL8256.
WARNING:root:No data on Impala for flight LGL62PM.
WARNING:root:No data on Impala for flight LGL937.
WARNING:root:No data on Impala for flight LGL833.
WARNING:root:No data on Impala for flight LXA21V.
WARNING:root:No data on Impala for flight KER739.
WARNING:root:No data on Impala for flight AMC394.
WARNING:root:No data on Impala for flight VJT492.
WARNING:root:No data on Impala for flight VJT405.
WARNING:root:No data on Impala for flight VJT929.
WARNING:root:No data on Impala for flight AMC329.
WARNING:root:No data on Impala for flight VJT437.
WARNING:root:No data on Impala for flight AMC101.
WARNING:root:No data on Impala for flight VJT965.
WARNING:root:No data on Impala for flight T7STK.
WARNING:root:No data on Impala for flight TEU3.
WARNING:root:No data on Impala for flight CTN29F.
WARNING:root:No data on Impala for flight CTN476.
WARNING:root:No data on Impala for flight AMC421.
WARNING:root:No data on Impala for flight T7STK.
WARNING:root:No data on Impala for flight CTN52R.
WARNING:root:No data on Impala for flight CTN71F.
WARNING:root:No data on Impala for flight CTN25F.
WARNING:root:No data on Impala for flight CTN475.
WARNING:root:No data on Impala for flight PRI545.
WARNING:root:No data on Impala for flight PRW368.
WARNING:root:No data on Impala for flight EZY892U.
WARNING:root:No data on Impala for flight TCX7RE.
WARNING:root:No data on Impala for flight TCX1325.
WARNING:root:No data on Impala for flight TCX1823.
WARNING:root:No data on Impala for flight CFG2FL.
WARNING:root:No data on Impala for flight TAR734.
WARNING:root:No data on Impala for flight PRW778.
WARNING:root:No data on Impala for flight TAR440.
WARNING:root:No data on Impala for flight TAR634.
WARNING:root:No data on Impala for flight CFG2CY.
WARNING:root:No data on Impala for flight TCX1512.
WARNING:root:No data on Impala for flight TAR735.
WARNING:root:No data on Impala for flight TCX1077.
WARNING:root:No data on Impala for flight CFG2XH.
WARNING:root:No data on Impala for flight TCX69RH.
WARNING:root:No data on Impala for flight TCX16VC.
WARNING:root:No data on Impala for flight TCX56RM.
WARNING:root:No data on Impala for flight OMA132.
WARNING:root:No data on Impala for flight UPEM007.
WARNING:root:No data on Impala for flight JAF3384.
WARNING:root:No data on Impala for flight JAF3383.
WARNING:root:No data on Impala for flight SVA126.
WARNING:root:No data on Impala for flight SVA117.
WARNING:root:No data on Impala for flight SVA115.
WARNING:root:No data on Impala for flight SVA7021.
WARNING:root:No data on Impala for flight KAL915.
WARNING:root:No data on Impala for flight SVA144.
WARNING:root:No data on Impala for flight IRM106.
WARNING:root:No data on Impala for flight IAW239.
WARNING:root:No data on Impala for flight SVA123.
WARNING:root:No data on Impala for flight SVA124.
WARNING:root:No data on Impala for flight IRM107.
WARNING:root:No data on Impala for flight ELY325.
WARNING:root:No data on Impala for flight ELY226.
WARNING:root:No data on Impala for flight ELY320.
WARNING:root:No data on Impala for flight ELY319.
WARNING:root:No data on Impala for flight ELY328.
WARNING:root:No data on Impala for flight ELY323.
WARNING:root:No data on Impala for flight ELY324.
WARNING:root:No data on Impala for flight ELY026.
WARNING:root:No data on Impala for flight RJA111.
WARNING:root:No data on Impala for flight RJA268.
WARNING:root:No data on Impala for flight RJA126.
WARNING:root:No data on Impala for flight RJA262.
WARNING:root:No data on Impala for flight RJA264.
WARNING:root:No data on Impala for flight MEA211.
WARNING:root:No data on Impala for flight MEA212.
WARNING:root:No data on Impala for flight MEA210.
WARNING:root:No data on Impala for flight SIA335.
WARNING:root:No data on Impala for flight AIC143.
WARNING:root:No data on Impala for flight JAI123.
WARNING:root:No data on Impala for flight THA931.
WARNING:root:No data on Impala for flight GFA018.
WARNING:root:No data on Impala for flight UAE214.
WARNING:root:No data on Impala for flight HVN10.
WARNING:root:No data on Impala for flight HVN18.
WARNING:root:No data on Impala for flight UAE72.
WARNING:root:No data on Impala for flight ETD97G.
WARNING:root:No data on Impala for flight UAE93P.
WARNING:root:No data on Impala for flight ETD47N.
WARNING:root:No data on Impala for flight UAE74.
WARNING:root:No data on Impala for flight ETD11K.
WARNING:root:No data on Impala for flight UAL90.
WARNING:root:No data on Impala for flight EVA088.
WARNING:root:No data on Impala for flight N1624K.
WARNING:root:No data on Impala for flight N375WB.
WARNING:root:No data on Impala for flight SJE500.
WARNING:root:No data on Impala for flight CMBDQ1.
WARNING:root:No data on Impala for flight N79MA.
WARNING:root:No data on Impala for flight N329CH.
WARNING:root:No data on Impala for flight FDX5238.
WARNING:root:No data on Impala for flight CKS9557.
WARNING:root:No data on Impala for flight LAN705.
WARNING:root:No data on Impala for flight N815WH.
WARNING:root:No data on Impala for flight TSC300.
WARNING:root:No data on Impala for flight N9997X.

with plt.style.context('traffic'):
    fig = plt.figure()
    ax = plt.axes(projection=EuroPP())

    ax.add_feature(countries())
    ax.gridlines()
    ax.set_extent((-10, 15, 35, 55))

    nm_airspaces['LFBBBDX'].plot(ax, lw=2, alpha=.5)

    for _, flight in so6_bdx_noon:
        flight.plot(ax, color='#aa3a3a', lw=.4, alpha=.5)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2747949891.py in <module>
     10     ax.set_extent((-10, 15, 35, 55))
     11 
---> 12     nm_airspaces['LFBBBDX'].plot(ax, lw=2, alpha=.5)
     13 
     14     for _, flight in so6_bdx_noon:

NameError: name 'nm_airspaces' is not defined

from traffic.data import eurofirs
# LISBOA FIR
eurofirs["EGPX"].geoencode() # This is the UK Airspace

opensky.api_tracks(flight.icao24)

import plotly.graph_objects as go
import pandas as pd

df_airports = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')
df_airports.head()

df_flight_paths = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_aa_flight_paths.csv')
df_flight_paths.head()

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'Europe',
    lon = df_airports['long'],
    lat = df_airports['lat'],
    hoverinfo = 'text',
    text = df_airports['airport'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

lons = []
lats = []
import numpy as np
lons = np.empty(3 * len(df_flight_paths))
lons[::3] = df_flight_paths['start_lon']
lons[1::3] = -4.433060
lons[2::3] = None
lats = np.empty(3 * len(df_flight_paths))
lats[::3] = df_flight_paths['start_lat']
lats[1::3] = 55.871899
lats[2::3] = None

fig.add_trace(
    go.Scattergeo(
        locationmode = 'Europe',
        lon = lons,
        lat = lats,
        mode = 'lines',
        line = dict(width = 1,color = 'red'),
        opacity = 0.5
    )
)

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = go.layout.Geo(
        scope = 'north america',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
    height=700,
)

fig.show()

28362	Glasgow International Airport	GLA	EGPF	55.871899	-4.433060	United Kingdom	26.0	large_airport	Paisley, Renfrewshire

dfCAC.head(5)

	firstSeen	lastSeen	icao24	callsign	estDepartureAirport	estArrivalAirport	registration	manufacturericao	manufacturername	model	...	home_link	wikipedia_link_x	keywords_x	id_y	code	name_y	continent_y	wikipedia_link_y	keywords_y	date
0	2021-10-17 09:39:17+00:00	2021-10-17 12:45:24+00:00	407567	EZY96EM	LEMG	EGPF	NaN	NaN	NaN	NaN	...	https://www.aena.es/en/malaga-costa-del-sol.html	https://en.wikipedia.org/wiki/M%C3%A1laga_Airport	Costa del Sol,Malaga	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17
1	2021-10-17 10:27:12+00:00	2021-10-17 13:19:21+00:00	407177	EXS8HQ	LEAL	EGPF	NaN	NaN	NaN	NaN	...	https://www.aena.es/en/alicante-elche.html	https://en.wikipedia.org/wiki/Alicante_Airport	NaN	302684	ES	Spain	EU	https://en.wikipedia.org/wiki/Spain	Aeropuertos de España	2021-10-17
2	2021-10-17 12:23:38+00:00	2021-10-17 13:22:08+00:00	4063de	SHT6R	EGLL	EGPF	G-EUYJ	AIRBUS	Airbus Sas	AIRBUS A320-232	...	http://www.heathrowairport.com/	https://en.wikipedia.org/wiki/Heathrow_Airport	LON, Londres	302688	GB	United Kingdom	EU	https://en.wikipedia.org/wiki/United_Kingdom	Great Britain	2021-10-17
3	2021-10-17 12:46:14+00:00	2021-10-17 13:35:59+00:00	400dc2	GMA03	NaN	EGPF	G-SASC	RAYTHEON	Raytheon Aircraft Company	BEECH B200C Super Kingair	...	NaN	NaN	NaN	302591	NaN	Namibia	AF	https://en.wikipedia.org/wiki/Namibia	NaN	2021-10-17
4	2021-10-17 13:01:09+00:00	2021-10-17 13:38:37+00:00	4ca61d	RYR5774	EIDW	EGPF	EI-DWP	BOEING	The Boeing Company	BOEING 737-8AS	...	http://www.dublinairport.com/	https://en.wikipedia.org/wiki/Dublin_Airport	Aerfort Bhaile Átha Cliath	302694	IE	Ireland	EU	https://en.wikipedia.org/wiki/Ireland	Eire	2021-10-17

5 rows × 58 columns

px.set_mapbox_access_token('mapbox_token')
fig = px.scatter_mapbox(dfCAC,
                        lat=df['coordinates.latitude'],
                        lon=df['coordinates.longitude'],
                        color='rating', # This assigns a color scale based on business rating
                        size='review_count', # Bigger circles = more reviews
                        color_discrete_sequence=px.colors.qualitative.Antique, # this sets up a colorscale with qualitative breaks for each value
                        size_max=25, # This sets an upper limit for the circle size
                        hover_name=df.name, # Name will pop up when you hover over the point on the map
                        mapbox_style='carto-positron', # I re-assigned the style to something a bit easier to read
                       zoom=9,) # This zoom level seems okay, though I should reset my default view location.
fig.show()

https://www.mit.edu/~amidi/teaching/data-science-tools/tutorial/data-manipulation-with-python/

https://buildmedia.readthedocs.org/media/pdf/traffic-viz/stable/traffic-viz.pdf

dfCAC.to_csv(r'GLA_Flights_Appended.csv')

mapbox_token='pk.eyJ1IjoiYWxpY2lhYWRhbXMiLCJhIjoiY2thZWJpaXI3MDJ4NjJwbHF1NWplZm9hbiJ9.lebaFcBpBTMGSNJmwWo3PA' 
    #this is my mapbox token

px.set_mapbox_access_token('mapbox_token') # Refer to Mapbox token
fig = px.scatter_mapbox(dfCAC,
                        lat=dfCAC['latitude_deg'], # telling it where the longitude and latitude live in the dataframe table
                        lon=dfCAC['longitude_deg'],
                        hover_name=dfCAC.date, # tell me the name of the business when I hover over it
                        mapbox_style='carto-darkmatter', # I re-assigned the style so I can see what's going on
                       zoom=10,) # I set a default zoom to 10
fig.show()

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'ISO-3',
    lon = dfCAC['longitude_deg'],
    lat = dfCAC['latitude_deg'],
    hoverinfo = 'name',
    text = dfCAC['date'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

lons = []
lats = []
import numpy as np
lons = np.empty(3 * len(dfCAC))
lons[::3] = dfCAC['longitude_deg']
lons[1::3] = dfCAC['destlong']
lons[2::3] = None
lats = np.empty(3 * len(dfCAC))
lats[::3] = dfCAC['latitude_deg']
lats[1::3] = dfCAC['destlat']
lats[2::3] = None

fig.add_trace(
    go.Scattergeo(
        locationmode = 'ISO-3',
        lon = lons,
        lat = lats,
        mode = 'lines',
        line = dict(width = 1,color = 'red'),
        opacity = 0.5
    )
)

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = go.layout.Geo(
        scope = 'world',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
    height=700,
)

fig.show()

https://aeriaa.com/estimating-aviation-co2-emissions-real-time-big-data/

df7.to_csv(r'EGPF_Flights.csv')

https://www.mit.edu/~amidi/teaching/data-science-tools/tutorial/data-manipulation-with-python/#

Folium

# 28362	Glasgow International Airport	GLA	EGPF	55.871899	-4.433060	United Kingdom	26.0	large_airport	Paisley, Renfrewshire
import folium
m=folium.Map(location=[55.871899, -4.433060])
m

Make this Notebook Trusted to load map: File -> Trust Notebook

f1=folium.FeatureGroup("Vehicle 1")
f2=folium.FeatureGroup("Vehicle 2")
f3=folium.FeatureGroup("Vehicle 3")

# Adding lines to the different feature groups
line_1=folium.vector_layers.PolyLine(coords_1,popup='<b>Path of Vehicle_1</b>',tooltip='Vehicle_1',color='blue',weight=10).add_to(f1)
line_2=folium.vector_layers.PolyLine(coords_2,popup='<b>Path of Vehicle_2</b>',tooltip='Vehicle_2',color='red',weight=10).add_to(f2)
line_3=folium.vector_layers.PolyLine(coords_3,popup='<b>Path of Vehicle_3</b>',tooltip='Vehicle_3',color='green',weight=10).add_to(f3)

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'country names',
    lon = dfCAC['longitude_deg'],
    lat = dfCAC['latitude_deg'],
    hoverinfo = 'name',
    text = dfCAC['date'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

flight_paths = []
for i in range(len(dfCAC)):
    fig.add_trace(
        go.Scattergeo(
            locationmode = 'USA-states',
            lon = [dfCAC['longitude_deg'][i], dfCAC['destlong'][i]],
            lat = [dfCAC['latitude_deg'][i], dfCAC['destlat'][i]],
            mode = 'lines',
            line = dict(width = 1,color = 'red'),
            opacity = .5,
        )
    )

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = dict(
        scope = 'world',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
)

fig.show()

float(dfCAC['date2'][i]) / float(dfCAC['date2'].max())

# import plotly.express as px
df = px.data.gapminder().query("continent == 'Oceania'")
fig = px.line(df, x='year', y='lifeExp', color='country')
fig.show()

my_pivot = dfCAC.pivot_table(index = 'estDepartureAirport', 
                          columns = 'estDepartureAirport', 
                          fill_value = 0, 
                          aggfunc={'estDepartureAirport':len})['estDepartureAirport']
my_pivot.plot.bar()
plt.tight_layout()
plt.show()

dfCACCT = dfCAC['name_y'].value_counts()

dfCACCT2=dfCACCT.to_frame()
dfCACCT2

	name_y
United Kingdom	918
Namibia	362
Ireland	97
Netherlands	89
Spain	78
Germany	43
France	27
Portugal	23
Poland	20
Jersey	17
United Arab Emirates	16
Denmark	14
Italy	11
Switzerland	11
Greece	11
Cyprus	10
United States	8
Sweden	6
Belgium	4
Hungary	4
Saudi Arabia	3
Slovenia	3
Czech Republic	2
Luxembourg	2
Russia	2
Malta	2
Thailand	2
Turkey	2
Japan	2
Australia	1
South Korea	1
Morocco	1
Iceland	1
Austria	1
Croatia	1
Bulgaria	1
Guinea-Bissau	1
Bangladesh	1
Isle of Man	1
Malaysia	1

dfCACCT2.reset_index

<bound method DataFrame.reset_index of                       name_y
United Kingdom           918
Namibia                  362
Ireland                   97
Netherlands               89
Spain                     78
Germany                   43
France                    27
Portugal                  23
Poland                    20
Jersey                    17
United Arab Emirates      16
Denmark                   14
Italy                     11
Switzerland               11
Greece                    11
Cyprus                    10
United States              8
Sweden                     6
Belgium                    4
Hungary                    4
Saudi Arabia               3
Slovenia                   3
Czech Republic             2
Luxembourg                 2
Russia                     2
Malta                      2
Thailand                   2
Turkey                     2
Japan                      2
Australia                  1
South Korea                1
Morocco                    1
Iceland                    1
Austria                    1
Croatia                    1
Bulgaria                   1
Guinea-Bissau              1
Bangladesh                 1
Isle of Man                1
Malaysia                   1>

dfCACCT2 = dfCACCT2.rename(columns = {'Country':'Flights'})

# Checking my work
print(dfCACCT2)

              Unnamed: 0  name_y
0         United Kingdom     918
1                Namibia     362
2                Ireland      97
3            Netherlands      89
4                  Spain      78
5                Germany      43
6                 France      27
7               Portugal      23
8                 Poland      20
9                 Jersey      17
10  United Arab Emirates      16
11               Denmark      14
12                 Italy      11
13           Switzerland      11
14                Greece      11
15                Cyprus      10
16         United States       8
17                Sweden       6
18               Belgium       4
19               Hungary       4
20          Saudi Arabia       3
21              Slovenia       3
22        Czech Republic       2
23            Luxembourg       2
24                Russia       2
25                 Malta       2
26              Thailand       2
27                Turkey       2
28                 Japan       2
29             Australia       1
30           South Korea       1
31               Morocco       1
32               Iceland       1
33               Austria       1
34               Croatia       1
35              Bulgaria       1
36         Guinea-Bissau       1
37            Bangladesh       1
38           Isle of Man       1
39              Malaysia       1

dfCACCT2.to_csv(r'flightfreqcountry.csv')

dfCACCT2 = pd.read_csv('flightfreqcountry.csv')
dfCACCT2

	Unnamed: 0	name_y
0	United Kingdom	918
1	Namibia	362
2	Ireland	97
3	Netherlands	89
4	Spain	78
5	Germany	43
6	France	27
7	Portugal	23
8	Poland	20
9	Jersey	17
10	United Arab Emirates	16
11	Denmark	14
12	Italy	11
13	Switzerland	11
14	Greece	11
15	Cyprus	10
16	United States	8
17	Sweden	6
18	Belgium	4
19	Hungary	4
20	Saudi Arabia	3
21	Slovenia	3
22	Czech Republic	2
23	Luxembourg	2
24	Russia	2
25	Malta	2
26	Thailand	2
27	Turkey	2
28	Japan	2
29	Australia	1
30	South Korea	1
31	Morocco	1
32	Iceland	1
33	Austria	1
34	Croatia	1
35	Bulgaria	1
36	Guinea-Bissau	1
37	Bangladesh	1
38	Isle of Man	1
39	Malaysia	1

Treechart

sizes=dfCACCT2['name_y']
label=dfCACCT2['Unnamed: 0']
squarify.plot(sizes=sizes, label=label, alpha=0.6 )
plt.axis('off')
plt.show()

dataAssists = dfCACCT2[dfCACCT2["name_y"]>5]

norm = matplotlib.colors.Normalize(vmin=min(dataAssists.name_y), vmax=max(dataAssists.name_y))
colors = [matplotlib.cm.Blues(norm(value)) for value in dataAssists.name_y]

fig = matplotlib.pyplot.gcf()
fig.set_size_inches(16, 4.5)

fig = plt.gcf()
fig.set_size_inches(16, 4.5)

squarify.plot(label=dataAssists['Unnamed: 0'],sizes=dataAssists['name_y'], color = colors, alpha=.6)
plt.title("Flights by Country (greater than 5)",fontsize=23,fontweight="bold")

plt.axis('off')
plt.show()

Okay, so there can't possibly be that many flights from Namibia.

After some investigation, it appears the country code for Namibia is "NA" - so when I joined the data, the blank cell must have coded as NA or NAN, miscoding as Namibia.

Let's see if I can clean this data.

Cleaning the Data

There are 362 entries that don't have an estimated departure airport. I tried calling a few of these to see if there was supplemental data contained in the aircraft database. Unfortunately, this is not the case; each search turns up empty.

# I tried calling a few different a
aircraft['EXS32TE']

	icao24	registration	typecode	serialnumber	model	operator	operatoricao	owner

for col in dfCAC.columns:
    print(col)

firstSeen
lastSeen
icao24
callsign
estDepartureAirport
estArrivalAirport
registration
manufacturericao
manufacturername
model
typecode
serialnumber
linenumber
icaoaircrafttype
operator
operatorcallsign
operatoricao
operatoriata
owner
testreg
registered
reguntil
status
built
firstflightdate
seatconfiguration
engines
modes
adsb
acars
notes
categoryDescription
day
id_x
ident
type
name_x
latitude_deg
longitude_deg
elevation_ft
continent_x
iso_country
iso_region
municipality
scheduled_service
gps_code
iata_code
local_code
home_link
wikipedia_link_x
keywords_x
id_y
code
name_y
continent_y
wikipedia_link_y
keywords_y
date
destlat
destlong
date2

dfCAC.isna().sum()

# Only one icao24 null entry. Great.

firstSeen                0
lastSeen                 0
icao24                   0
callsign                 0
estDepartureAirport    362
                      ... 
keywords_y             403
date                     0
destlat                  0
destlong                 0
date2                    0
Length: 61, dtype: int64

# dfCAC = dfCAC.drop(columns=['registered', 'reguntil'])

# dfCAC = dfCAC.drop(columns=['firstflightdate', 'seatconfiguration'])

# dfCAC = dfCAC.drop(columns=['linenumber', 'operatoriata'])

# dfCAC = dfCAC.drop(columns=['status', 'built'])

# dfCAC = dfCAC.drop(columns=['notes', 'elevation_ft'])

# dfCAC = dfCAC.drop(columns=['scheduled_service'])

# dfCAC = dfCAC.drop(columns=['modes','adsb','acars','local_code','id_y','keywords_y'])

dfCAC = dfCAC.drop(columns=['keywords_x'])

for col in dfCAC.columns:
    print(col)

firstSeen
lastSeen
icao24
callsign
estDepartureAirport
estArrivalAirport
registration
manufacturericao
manufacturername
model
typecode
serialnumber
icaoaircrafttype
operator
operatorcallsign
operatoricao
owner
engines
categoryDescription
day
id_x
ident
type
name_x
latitude_deg
longitude_deg
continent_x
iso_country
iso_region
municipality
gps_code
iata_code
home_link
wikipedia_link_x
code
name_y
continent_y
wikipedia_link_y
date
destlat
destlong
date2

Codes = pd.read_csv('Country_Codes.csv')
Codes.head(5)

	English short name lower case	Alpha-2 code	Alpha-3 code	Numeric code	ISO 3166-2
0	Afghanistan	AF	AFG	4	ISO 3166-2:AF
1	Åland Islands	AX	ALA	248	ISO 3166-2:AX
2	Albania	AL	ALB	8	ISO 3166-2:AL
3	Algeria	DZ	DZA	12	ISO 3166-2:DZ
4	American Samoa	AS	ASM	16	ISO 3166-2:AS

Codes['Country']=Codes['English short name lower case']

Codes

	English short name lower case	Alpha-2 code	Alpha-3 code	Numeric code	ISO 3166-2	Country
0	Afghanistan	AF	AFG	4	ISO 3166-2:AF	Afghanistan
1	Åland Islands	AX	ALA	248	ISO 3166-2:AX	Åland Islands
2	Albania	AL	ALB	8	ISO 3166-2:AL	Albania
3	Algeria	DZ	DZA	12	ISO 3166-2:DZ	Algeria
4	American Samoa	AS	ASM	16	ISO 3166-2:AS	American Samoa
...	...	...	...	...	...	...
241	Wallis and Futuna	WF	WLF	876	ISO 3166-2:WF	Wallis and Futuna
242	Western Sahara	EH	ESH	732	ISO 3166-2:EH	Western Sahara
243	Yemen	YE	YEM	887	ISO 3166-2:YE	Yemen
244	Zambia	ZM	ZMB	894	ISO 3166-2:ZM	Zambia
245	Zimbabwe	ZW	ZWE	716	ISO 3166-2:ZW	Zimbabwe

246 rows × 6 columns

DelEm = pd.read_csv('CountryTravelEmissions.csv')
DelEm.head(5)

	Country	TotalCO2
0	Nicaragua	2.5960
1	North Korea	1.9400
2	Liberia	1.2850
3	Bolivia	2.3047
4	Chad	2.4989

demc = pd.merge(DelEm, Codes, how='left', on='Country')
demc

	Country	TotalCO2	English short name lower case	Alpha-2 code	Alpha-3 code	Numeric code	ISO 3166-2
0	Nicaragua	2.5960	Nicaragua	NI	NIC	558.0	ISO 3166-2:NI
1	North Korea	1.9400	North Korea	KR	KOR	410.0	ISO 3166-2:KR
2	Liberia	1.2850	Liberia	LR	LBR	430.0	ISO 3166-2:LR
3	Bolivia	2.3047	Bolivia	BO	BOL	68.0	ISO 3166-2:BO
4	Chad	2.4989	Chad	TD	TCD	148.0	ISO 3166-2:TD
...	...	...	...	...	...	...	...
193	United Kingdom	0.1574	United Kingdom	GB	GBR	826.0	ISO 3166-2:GB
194	Netherlands	0.1902	Netherlands	NL	NLD	528.0	ISO 3166-2:NL
195	France	0.2056	France	FR	FRA	250.0	ISO 3166-2:FR
196	Ireland	0.8720	Ireland	IE	IRL	372.0	ISO 3166-2:IE
197	NaN	330.1450	NaN	NaN	NaN	NaN	NaN

198 rows × 7 columns

demc.to_csv(r'DelegateEmissionsCoded.csv')

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(demc, locations='Alpha-3 code', color='TotalCO2',
                           color_continuous_scale="Plasma",
                           range_color=(0, 3),
                           scope="world",
                           labels={'TotalCO2':'Total CO2 Emissions'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

demc = pd.read_csv('DelegateEmissionsCoded.csv')

df = px.data.gapminder().query("year==2007")
fig = px.choropleth(df, locations="iso_alpha",
                    color="lifeExp", # lifeExp is a column of gapminder
                    hover_name="country", # column to add to hover information
                    color_continuous_scale=px.colors.sequential.Plasma)
fig.show()

Delegate = pd.read_csv('DelegateEmissions.csv')
Delegate.head(5)

	Country	Origin (Default =\nSeat of Govt.)	Origin Airport	Destination Airport	tCO2e output for leg (round trip)	Origin Airport.1	Destination Airport.1	tCO2e output for leg (round trip).1	Origin Airport.2	Destination Airport.2	tCO2e output for leg (round trip).2	Origin Airport.3	Destination Airport.3	tCO2e output for leg (round trip).3	Code	Number of Delegates	TotalCO2	Legs
0	Nicaragua	Managua	MGA	MIA	0.3210	MIA	ZRH	1.6762	ZRH	ALC	0.2480	ALC	GLA	0.3508	NIC	5	12.9800	4
1	North Korea	Pyongyang	FNJ	PEK	0.3400	PEK	BRU	1.3280	BRU	AMS	0.0818	AMS	GLA	0.1902	PRK	3	5.8200	4
2	Liberia	Monrovia	ROB	BKO	0.1320	BKO	CDG	0.8422	CDG	AMS	0.1206	AMS	GLA	0.1902	LBR	105	134.9250	4
3	Bolivia	La Paz	LPB	VVI	0.1570	VVI	MAD	1.6949	MAD	AMS	0.2626	AMS	GLA	0.1902	BOL	25	57.6175	4
4	Chad	N'Djamena	NDJ	DLA	0.1965	DLA	ADD	1.0272	ADD	CDG	1.0696	CDG	GLA	0.2056	TCD	60	149.9340	4

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(Delegate, locations='Code', color='Number of Delegates',
                           color_continuous_scale="Plasma",
                           range_color=(0, 300),
                           scope="world",
                           labels={'Number of Delegates':'Number of Delegates'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(Delegate, locations='Code', color='TotalCO2',
                           color_continuous_scale="Plasma",
                           range_color=(0, 200),
                           scope="world",
                           labels={'TotalCO2':'Total CO2 Emissions'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

# df = px.data.gapminder()

fig = px.scatter(Delegate, x="Number of Delegates", y="TotalCO2",
        size="Number of Delegates", color="Legs",
                 hover_name="Country", log_x=True, size_max=60)
fig.show()

df = px.data.gapminder().query("year==2007")
fig = px.choropleth(df, locations="iso_alpha",
                    color="lifeExp", # lifeExp is a column of gapminder
                    hover_name="country", # column to add to hover information
                    color_continuous_scale=px.colors.sequential.Plasma)
fig.show()

Delegate = pd.read_csv('Delegates_Ed.csv')
Delegate.head(5)

	Country	Delegates	Code	CO2	Legs
0	Albania	14	ALB	6.9132	2
1	Algeria	14	DZA	18.3820	3
2	Andorra	8	AND	9.0224	2
3	Angola	71	AGO	80.4998	3
4	Antigua and Barbuda	26	ATG	49.6860	2

Number of Delegates

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(Delegate, locations='Code', color='Delegates',
                           color_continuous_scale="Reds",
                           range_color=(0, 300),
                           scope="world",
                           labels={'Delegates':'Number of Delegates'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

Legs of Trip

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(Delegate, locations='Code', color='Legs',
                           color_continuous_scale="Reds",
                           range_color=(0, 4),
                           scope="world",
                           labels={'Legs':'Legs'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

Total Emissions

# from urllib.request import urlopen
# import json
# with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
#     counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth(Delegate, locations='Code', color='CO2',
                           color_continuous_scale="Reds",
                           range_color=(0, 300),
                           scope="world",
                           labels={'CO2':'Total CO2 Emissions'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

from urllib.request import urlopen
import json
with urlopen('https://github.com/datasets/geo-countries/blob/cd9e0635901eac20294a57ee3b3ce0684d5e3f1a/data/countries.geojson') as response:
    countries = json.load(response)

Delegate_fips = pd.read_csv("Delegates_Ed.csv",
                   dtype={"CO2": str})

fig = px.choropleth_mapbox(Delegate, geojson=countries, locations='Code', color='CO2',
                           color_continuous_scale="Reds",
                           range_color=(0, 300),
                           mapbox_style="carto-positron",
                           zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
                           opacity=0.5,
                           labels={'CO2':'Total CO2 Emissions'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

---------------------------------------------------------------------------
JSONDecodeError                           Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2607912538.py in <module>
      2 import json
      3 with urlopen('https://github.com/datasets/geo-countries/blob/cd9e0635901eac20294a57ee3b3ce0684d5e3f1a/data/countries.geojson') as response:
----> 4     countries = json.load(response)
      5 
      6 Delegate_fips = pd.read_csv("Delegates_Ed.csv",

~/opt/anaconda3/envs/Flights/lib/python3.9/json/__init__.py in load(fp, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    291     kwarg; otherwise ``JSONDecoder`` is used.
    292     """
--> 293     return loads(fp.read(),
    294         cls=cls, object_hook=object_hook,
    295         parse_float=parse_float, parse_int=parse_int,

~/opt/anaconda3/envs/Flights/lib/python3.9/json/__init__.py in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    344             parse_int is None and parse_float is None and
    345             parse_constant is None and object_pairs_hook is None and not kw):
--> 346         return _default_decoder.decode(s)
    347     if cls is None:
    348         cls = JSONDecoder

~/opt/anaconda3/envs/Flights/lib/python3.9/json/decoder.py in decode(self, s, _w)
    335 
    336         """
--> 337         obj, end = self.raw_decode(s, idx=_w(s, 0).end())
    338         end = _w(s, end).end()
    339         if end != len(s):

~/opt/anaconda3/envs/Flights/lib/python3.9/json/decoder.py in raw_decode(self, s, idx)
    353             obj, end = self.scan_once(s, idx)
    354         except StopIteration as err:
--> 355             raise JSONDecodeError("Expecting value", s, err.value) from None
    356         return obj, end

JSONDecodeError: Expecting value: line 7 column 1 (char 6)

from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

# import pandas as pd
# df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
#                    dtype={"fips": str})

# import plotly.express as px

fig = px.choropleth_mapbox(df, geojson=counties, locations='fips', color='unemp',
                           color_continuous_scale="Viridis",
                           range_color=(0, 12),
                           mapbox_style="carto-positron",
                           zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
                           opacity=0.5,
                           labels={'unemp':'unemployment rate'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

Failed Tests

val = dfCAC.groupby(['day']).size()

dfCAC2 = pd.pivot_table(dfCAC, values='callsign', index=['date'],columns='estDepartureAirport', aggfunc=np.sum)

# ploty
fig = go.Figure()
for col in dfCAC2.columns:
    fig.add_trace(go.Scatter(x=dfCAC2.index, y=dfCAC2[col].values,
                             name = col,
                             mode = 'markers+lines',
                             line=dict(shape='linear'),
                             connectgaps=True
                             )
                 )
fig.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/3309764950.py in <module>
      6 fig = go.Figure()
      7 for col in dfCAC2.columns:
----> 8     fig.add_trace(go.Scatter(x=dfCAC2.index, y=val,
      9                              name = col,
     10                              mode = 'markers+lines',

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/graph_objs/_scatter.py in __init__(self, arg, cliponaxis, connectgaps, customdata, customdatasrc, dx, dy, error_x, error_y, fill, fillcolor, groupnorm, hoverinfo, hoverinfosrc, hoverlabel, hoveron, hovertemplate, hovertemplatesrc, hovertext, hovertextsrc, ids, idssrc, legendgroup, legendgrouptitle, legendrank, line, marker, meta, metasrc, mode, name, opacity, orientation, selected, selectedpoints, showlegend, stackgaps, stackgroup, stream, text, textfont, textposition, textpositionsrc, textsrc, texttemplate, texttemplatesrc, uid, uirevision, unselected, visible, x, x0, xaxis, xcalendar, xhoverformat, xperiod, xperiod0, xperiodalignment, xsrc, y, y0, yaxis, ycalendar, yhoverformat, yperiod, yperiod0, yperiodalignment, ysrc, **kwargs)
   3126         _v = name if name is not None else _v
   3127         if _v is not None:
-> 3128             self["name"] = _v
   3129         _v = arg.pop("opacity", None)
   3130         _v = opacity if opacity is not None else _v

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in __setitem__(self, prop, value)
   4817                 # ### Handle simple property ###
   4818                 else:
-> 4819                     self._set_prop(prop, value)
   4820             else:
   4821                 # Make sure properties dict is initialized

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in _set_prop(self, prop, val)
   5161                 return
   5162             else:
-> 5163                 raise err
   5164 
   5165         # val is None

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in _set_prop(self, prop, val)
   5156 
   5157         try:
-> 5158             val = validator.validate_coerce(val)
   5159         except ValueError as err:
   5160             if self._skip_invalid:

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/_plotly_utils/basevalidators.py in validate_coerce(self, v)
   1101                     v = str(v)
   1102                 else:
-> 1103                     self.raise_invalid_val(v)
   1104 
   1105             if self.no_blank and len(v) == 0:

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/_plotly_utils/basevalidators.py in raise_invalid_val(self, v, inds)
    287                 name += "[" + str(i) + "]"
    288 
--> 289         raise ValueError(
    290             """
    291     Invalid value of type {typ} received for the '{name}' property of {pname}

ValueError: 
    Invalid value of type 'builtins.tuple' received for the 'name' property of scatter
        Received value: ('day', 'BIKF')

    The 'name' property is a string and must be specified as:
      - A string
      - A number that will be converted to a string

Delegate = pd.read_csv('DelegateEmissions.csv')
Delegate.head(5)

	Country	Origin (Default =\nSeat of Govt.)	Origin Airport	Destination Airport	tCO2e output for leg (round trip)	Origin Airport.1	Destination Airport.1	tCO2e output for leg (round trip).1	Origin Airport.2	Destination Airport.2	tCO2e output for leg (round trip).2	Origin Airport.3	Destination Airport.3	tCO2e output for leg (round trip).3	Code	Number of Delegates	TotalCO2	Legs
0	Nicaragua	Managua	MGA	MIA	0.3210	MIA	ZRH	1.6762	ZRH	ALC	0.2480	ALC	GLA	0.3508	NIC	5	12.9800	4
1	North Korea	Pyongyang	FNJ	PEK	0.3400	PEK	BRU	1.3280	BRU	AMS	0.0818	AMS	GLA	0.1902	PRK	3	5.8200	4
2	Liberia	Monrovia	ROB	BKO	0.1320	BKO	CDG	0.8422	CDG	AMS	0.1206	AMS	GLA	0.1902	LBR	105	134.9250	4
3	Bolivia	La Paz	LPB	VVI	0.1570	VVI	MAD	1.6949	MAD	AMS	0.2626	AMS	GLA	0.1902	BOL	25	57.6175	4
4	Chad	N'Djamena	NDJ	DLA	0.1965	DLA	ADD	1.0272	ADD	CDG	1.0696	CDG	GLA	0.2056	TCD	60	149.9340	4

demc = pd.read_csv('DelegateEmissionsCoded.csv')

df = px.data.gapminder().query("year==2007")
fig = px.choropleth(df, locations="iso_alpha",
                    color="lifeExp", # lifeExp is a column of gapminder
                    hover_name="country", # column to add to hover information
                    color_continuous_scale=px.colors.sequential.Plasma)
fig.show()

temp = dfCAC('estDepartureAirport').value_counts()
temp2 = temp.head(10)
if len(temp) > 10:
    temp2['remaining {0} items'.format(len(temp) - 10)] = sum(temp[10:])
temp2.plot(kind='bar')

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/3210483220.py in <module>
----> 1 temp = dfCAC('estDepartureAirport').value_counts()
      2 temp2 = temp.head(10)
      3 if len(temp) > 10:
      4     temp2['remaining {0} items'.format(len(temp) - 10)] = sum(temp[10:])
      5 temp2.plot(kind='bar')

TypeError: 'DataFrame' object is not callable

us_cities = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/us-cities-top-1k.csv")
us_cities = us_cities.query("State in ['New York', 'Ohio']")

fig = px.line_mapbox(us_cities, lat="lat", lon="lon", color="State", zoom=3, height=300)

fig.update_layout(mapbox_style="stamen-terrain", mapbox_zoom=4, mapbox_center_lat = 41,
    margin={"r":0,"t":0,"l":0,"b":0})

fig.show()

with plt.style.context("traffic"):
    fig, ax = plt.subplots(subplot_kw=dict(projection=Lambert93()))
    ax.background_patch.set_visible(False)
    ax.spines['geo'].set_visible(False)

    # We may add contours from OpenStreetMap
    # (Occitanie is the name of the administrative region)
    Nominatim.search("Occitanie").plot(ax, linestyle="dotted")
    ax.set_extent("Occitanie")

    # Plot the airport, the TMA
    airports["LFBO"].plot(ax)
    lfbo_tma.plot(ax, linewidth=2, linestyle="dashed")

    # and the resulting traffic
    t_tma.plot(ax)

/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/776388163.py:3: DeprecationWarning: The background_patch property is deprecated. Use GeoAxes.patch instead.
  ax.background_patch.set_visible(False)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/776388163.py in <module>
      6     # We may add contours from OpenStreetMap
      7     # (Occitanie is the name of the administrative region)
----> 8     Nominatim.search("Occitanie").plot(ax, linestyle="dotted")
      9     ax.set_extent("Occitanie")
     10 

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/cartes/osm/nominatim.py in __getattr__(self, name)
     64                 value = address.get(name, None)
     65         if value is None:
---> 66             raise AttributeError(name)
     67         return value
     68 

AttributeError: plot

dt = dfCAC.groupby(['date']).size()
# dt.plot.line()
# df = px.data.gapminder().query("country=='Canada'")
fig = px.line(x=dfCAC['date'], y=dt, title='Life expectancy in Canada')
fig.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1262034092.py in <module>
      3 # dt.plot.line()
      4 # df = px.data.gapminder().query("country=='Canada'")
----> 5 fig = px.line(x=dfCAC['date'], y=dt, title='Life expectancy in Canada')
      6 fig.show()

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/express/_chart_types.py in line(data_frame, x, y, line_group, color, line_dash, symbol, hover_name, hover_data, custom_data, text, facet_row, facet_col, facet_col_wrap, facet_row_spacing, facet_col_spacing, error_x, error_x_minus, error_y, error_y_minus, animation_frame, animation_group, category_orders, labels, orientation, color_discrete_sequence, color_discrete_map, line_dash_sequence, line_dash_map, symbol_sequence, symbol_map, markers, log_x, log_y, range_x, range_y, line_shape, render_mode, title, template, width, height)
    258     a polyline mark in 2D space.
    259     """
--> 260     return make_figure(args=locals(), constructor=go.Scatter)
    261 
    262 

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/express/_core.py in make_figure(args, constructor, trace_patch, layout_patch)
   1931     apply_default_cascade(args)
   1932 
-> 1933     args = build_dataframe(args, constructor)
   1934     if constructor in [go.Treemap, go.Sunburst, go.Icicle] and args["path"] is not None:
   1935         args = process_dataframe_hierarchy(args)

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/express/_core.py in build_dataframe(args, constructor)
   1403     # now that things have been prepped, we do the systematic rewriting of `args`
   1404 
-> 1405     df_output, wide_id_vars = process_args_into_dataframe(
   1406         args, wide_mode, var_name, value_name
   1407     )

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/express/_core.py in process_args_into_dataframe(args, wide_mode, var_name, value_name)
   1243 
   1244                 if length and len(argument) != length:
-> 1245                     raise ValueError(
   1246                         "All arguments should have the same length. "
   1247                         "The length of argument `%s` is %d, whereas the "

ValueError: All arguments should have the same length. The length of argument `y` is 29, whereas the length of  previously-processed arguments ['x'] is 1800

fig = go.Figure()

# source_to_dest = zip(overseas_cnt_df["LatOrig"], overseas_cnt_df["LatDest"],
#                      overseas_cnt_df["LongOrig"], overseas_cnt_df["LongDest"],
#                      overseas_cnt_df["Num_Of_Flights"])

## Loop thorugh each flight entry to add line between source and destination
for latitude_deg,destlat,longitude_deg,destlong in dfCAC:
    fig.add_trace(go.Scattergeo(
                        lat = [latitude_deg, destlat],
                        lon = [longitude_deg, destlong],
                        mode = 'lines',
                        line = dict(3, color="red")
                        ))

## Logic to create labels of source and destination cities of flights
cities = dfCAC["municipality"].values.tolist()+'Glasgow'.values.tolist()
countries = dfCAC["iso_country"].values.tolist()+'Scotland'.values.tolist()
scatter_hover_data = [country + " : "+ city for city, country in zip(cities, countries)]

## Loop thorugh each flight entry to plot source and destination as points.
fig.add_trace(
    go.Scattergeo(
                lon = dfCAC['longitude_deg'].values.tolist()+ dfCAC['destlong'].values.tolist(),
                lat = dfCAC['latitude_deg'].values.tolist()+ dfCAC['destlat'].values.tolist(),
                hoverinfo = 'text',
                text = scatter_hover_data,
                mode = 'markers',
                marker = dict(size = 10, color = 'blue', opacity=0.1,))
    )

## Update graph layout to improve graph styling.
fig.update_layout(title_text="Connection Map Depicting Flights from Brazil to All Other Countries (Orthographic Projection)",
                  height=500, width=500,
                  margin={"t":0,"b":0,"l":0, "r":0, "pad":0},
                  showlegend=False,
                  geo= dict(projection_type = 'orthographic', showland = True, landcolor = 'lightgrey', countrycolor = 'grey'))

fig.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/1289736370.py in <module>
      6 
      7 ## Loop thorugh each flight entry to add line between source and destination
----> 8 for latitude_deg,destlat,longitude_deg,destlong in dfCAC:
      9     fig.add_trace(go.Scattergeo(
     10                         lat = [latitude_deg, destlat],

ValueError: too many values to unpack (expected 4)

wid = dfCAC.groupby(['estDepartureAirport']).size()

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'ISO-3',
    lon = dfCAC['longitude_deg'],
    lat = dfCAC['latitude_deg'],
    hoverinfo = 'name',
    text = dfCAC['date'],
    mode = 'markers',
    marker = dict(
        size = 3,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

lons = []
lats = []
import numpy as np
lons = np.empty(3 * len(dfCAC))
lons[::3] = dfCAC['longitude_deg']
lons[1::3] = dfCAC['destlong']
lons[2::3] = None
lats = np.empty(3 * len(dfCAC))
lats[::3] = dfCAC['latitude_deg']
lats[1::3] = dfCAC['destlat']
lats[2::3] = None

fig.add_trace(
    go.Scattergeo(
        locationmode = 'ISO-3',
        lon = lons,
        lat = lats,
        mode = 'lines',
        line = dict(width = wid,color = 'red'),
        opacity = 0.5
    )
)

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = go.layout.Geo(
        scope = 'world',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
    height=700,
)

fig.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2909318700.py in <module>
     32 
     33 fig.add_trace(
---> 34     go.Scattergeo(
     35         locationmode = 'ISO-3',
     36         lon = lons,

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/graph_objs/_scattergeo.py in __init__(self, arg, connectgaps, customdata, customdatasrc, featureidkey, fill, fillcolor, geo, geojson, hoverinfo, hoverinfosrc, hoverlabel, hovertemplate, hovertemplatesrc, hovertext, hovertextsrc, ids, idssrc, lat, latsrc, legendgroup, legendgrouptitle, legendrank, line, locationmode, locations, locationssrc, lon, lonsrc, marker, meta, metasrc, mode, name, opacity, selected, selectedpoints, showlegend, stream, text, textfont, textposition, textpositionsrc, textsrc, texttemplate, texttemplatesrc, uid, uirevision, unselected, visible, **kwargs)
   2216         _v = line if line is not None else _v
   2217         if _v is not None:
-> 2218             self["line"] = _v
   2219         _v = arg.pop("locationmode", None)
   2220         _v = locationmode if locationmode is not None else _v

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in __setitem__(self, prop, value)
   4809                 # ### Handle compound property ###
   4810                 if isinstance(validator, CompoundValidator):
-> 4811                     self._set_compound_prop(prop, value)
   4812 
   4813                 # ### Handle compound array property ###

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in _set_compound_prop(self, prop, val)
   5220         # ------------
   5221         validator = self._get_validator(prop)
-> 5222         val = validator.validate_coerce(val, skip_invalid=self._skip_invalid)
   5223 
   5224         # Save deep copies of current and new states

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/_plotly_utils/basevalidators.py in validate_coerce(self, v, skip_invalid, _validate)
   2465 
   2466         elif isinstance(v, dict):
-> 2467             v = self.data_class(v, skip_invalid=skip_invalid, _validate=_validate)
   2468 
   2469         elif isinstance(v, self.data_class):

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/graph_objs/scattergeo/_line.py in __init__(self, arg, color, dash, width, **kwargs)
    196         _v = width if width is not None else _v
    197         if _v is not None:
--> 198             self["width"] = _v
    199 
    200         # Process unknown kwargs

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in __setitem__(self, prop, value)
   4817                 # ### Handle simple property ###
   4818                 else:
-> 4819                     self._set_prop(prop, value)
   4820             else:
   4821                 # Make sure properties dict is initialized

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in _set_prop(self, prop, val)
   5161                 return
   5162             else:
-> 5163                 raise err
   5164 
   5165         # val is None

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/plotly/basedatatypes.py in _set_prop(self, prop, val)
   5156 
   5157         try:
-> 5158             val = validator.validate_coerce(val)
   5159         except ValueError as err:
   5160             if self._skip_invalid:

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/_plotly_utils/basevalidators.py in validate_coerce(self, v)
    804             # Check numeric
    805             if not isinstance(v, numbers.Number):
--> 806                 self.raise_invalid_val(v)
    807 
    808             # Check min/max

~/opt/anaconda3/envs/Flights/lib/python3.9/site-packages/_plotly_utils/basevalidators.py in raise_invalid_val(self, v, inds)
    287                 name += "[" + str(i) + "]"
    288 
--> 289         raise ValueError(
    290             """
    291     Invalid value of type {typ} received for the '{name}' property of {pname}

ValueError: 
    Invalid value of type 'pandas.core.series.Series' received for the 'width' property of scattergeo.line
        Received value: estDepartureAirport
BIKF     1
EBBR     3
EBCI     1
EDDB     2
EDDF    34
        ..
UUWW     2
VGZR     1
VTBS     2
WMKK     1
YSSY     1
Length: 120, dtype: int64

    The 'width' property is a number and may be specified as:
      - An int or float in the interval [0, inf]

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'ISO-3',
    lon = dfCAC['longitude_deg'],
    lat = dfCAC['latitude_deg'],
    hoverinfo = 'name',
    text = dfCAC['date'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

lons = []
lats = []
import numpy as np
lons = np.empty(3 * len(dfCAC))
lons[::3] = dfCAC['longitude_deg']
lons[1::3] = dfCAC['destlong']
lons[2::3] = None
lats = np.empty(3 * len(dfCAC))
lats[::3] = dfCAC['latitude_deg']
lats[1::3] = dfCAC['destlat']
lats[2::3] = None

fig.add_trace(
    go.Scattergeo(
        locationmode = 'ISO-3',
        lon = lons,
        lat = lats,
        mode = 'lines',
        line = dict(width = float(dfCAC.groupby([['estDepartureAirport']].size()),
                    color = 'red'),
        opacity = 0.5
    )
))

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = dict(
        scope = 'north america',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
)

fig.show()

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/3h/bwq485wx2y32mt9zm3l7sgfw0000gn/T/ipykernel_23474/2879884835.py in <module>
     35         lat = lats,
     36         mode = 'lines',
---> 37         line = dict(width = dfCAC.groupby([['estDepartureAirport']].size(),
     38                     color = 'red'),
     39         opacity = 0.5

AttributeError: 'list' object has no attribute 'size'

cumul = []
for flight in collection:
if flight.min("altitude") < 30000:
continue
cumul.append(flight.filter().resample("30s"))
new_collection = Traffic.from_flights(cumul)

from datetime import timedelta, date, time

def DateTimeRange(start_date, end_date):
     for n in range(0, int((end_date - start_date).days) + 1, 7):
         yield start_date + timedelta(n)

start_dt = datetime(2018, 9, 1)
end_dt = datetime(2018, 10, 30)
for dt in daterange(start_dt, end_dt):
    print(dt.strftime("%Y-%m-%d"))
    "%Y/%m/%d %H:%M"
    datetime.strptime
    DateTimeRange